SaaS development costs: what to expect when building beyond MVP

Most founders obsess over one question:

“How much will it cost to build the MVP?”

It’s a fair question. But if you stop there, you’re planning for maybe 30–40% of the total bill for the first 2–3 years of your SaaS – and ignoring the remaining 60–70% that actually decides whether your product survives.

Let’s unpack why:

What “MVP” usually includes (and what it doesn’t)

Every agency or developer defines MVP a bit differently, but in practice, an MVP typically covers:

• Core user flows (sign up, login, basic onboarding)
• The smallest set of features that solves a specific problem for a specific segment
• A “good enough” UI/UX – usable, not pixel-perfect
• A single production environment (maybe with a basic staging environment if you’re lucky)
• Minimal automation (few or no CI/CD pipelines, basic monitoring, basic logs)

Crucially, an MVP is optimised for speed and learning, not for:

• Long-term maintainability
• Fully hardened security and compliance
• Complex automation
• Heavy-load performance
• Multiple platforms (web + mobile)

That’s not a bad thing. It’s the point of an MVP. But it means the cost to get something into the world is fundamentally different from the cost to keep it alive, reliable, and improving.

The real cost starts when real users arrive

You don’t feel the true shape of SaaS development costs in development sprints. You feel it:

• When a paying customer hits a bug on a Friday night
• When a big prospect asks “Do you have SSO?”
• When you realise you’re manually onboarding every new user
• When customers start asking for integrations, mobile access, or custom workflows

At that point, your cost moves from a one-time “build” to ongoing monthly and quarterly commitments:

• Maintenance – fixing bugs, patching security issues, keeping dependencies fresh
• Hosting & infrastructure – cloud costs grow with usage, storage, and regions
• Support & success – tools, processes, and sometimes people to help users
• Iterative improvements – new features, UX fixes, onboarding improvements

If MVP is the downpayment on your product, all of this is your “mortgage”. Skip it and the product decays faster than you think.

A simple mental model: 30–40% vs 60–70%

Every product will be different, but a useful mental model for most B2B/B2C SaaS is:

• MVP build ≈ 30–40% of your total 2–3 year SaaS development cost
• Post-MVP (maintenance, hosting, support, iterative improvements) ≈ 60–70%

Very rough example over a ~2–3 year horizon:

• MVP build: €60k
• Post-MVP spend:
  • Maintenance & technical debt: €30–60k
  • Hosting/infra: €15–40k
  • Ongoing feature development & UX: €60–120k
  • Support-related dev & tools: €15–30k

Suddenly that “€60k MVP” is closer to €180–250k total once you include what it costs to keep the thing improving and generating revenue.

Again: the precise numbers will vary, but the ratio holds surprisingly often.

CAPEX mindset vs OPEX reality

Many founders treat MVP like CAPEX (capital expenditure):

“I pay once, I get an app, we’re done.”

SaaS doesn’t work like that. It behaves much more like OPEX (operational expenditure): a recurring investment that:

• Keeps your product working
• Makes it better quarter after quarter
• Enables you to ship features that actually move revenue and retention

Thinking in CAPEX terms leads to:

• Under-budgeting for maintenance (“we’ll fix it later”)
• Cutting corners on infra (“just leave the logging/monitoring for now”)
• Getting stuck with a codebase that’s hard to change
• Sudden “oh no, we need a full rewrite” moments 18 months in

Thinking in OPEX terms leads to:

• Planning a monthly or quarterly product budget, not just a build price
• Treating maintenance as a baseline requirement, not an optional luxury
• Ring-fencing time and budget for iterative improvements
• Making deliberate decisions about when to bring in a custom software development company as a long-term partner instead of just a “feature factory”

Your product becomes less of a one-off project and more of a living system with a predictable cost structure.

Why this matters even if you build in-house

You might think: “We’ll hire our own developers – the post-MVP cost problem disappears.”

It doesn’t. It just changes shape.

Whether you:

• Hire an in-house team,
• Work with a freelance network, or
• Partner with a custom software development company,

you still pay for:

• Developer and designer time to keep shipping
• Time spent on maintenance, security, and infra
• Time spent on product discovery and prioritisation
• Time spent fixing issues that stem from early compromises

In-house teams often feel cheaper because you’re not seeing a project invoice, but:

• Salaries + taxes + benefits are a fixed monthly burn, regardless of what gets shipped
• If the team spends 60% of their time firefighting a fragile MVP, your effective cost per meaningful feature skyrockets

The model is the same: MVP is your entry ticket, and the ongoing work is what determines whether you reach product-market fit and revenue.

Why agencies like VeryCreatives think beyond MVP

A lot of agencies are optimised purely for MVPs: fast builds, nice case studies, on to the next project.

That’s not where most of your costs – or your success – actually sit.

A partner who genuinely understands SaaS will:

• Scope your MVP with the next 1–3 years in mind (tech stack, architecture, roadmap)
• Help you plan what happens the day after launch – maintenance, hosting, support readiness
• Propose post-MVP collaboration models (like an essential maintenance layer plus a dedicated growth team) instead of disappearing after handoff

For non-technical founders especially, this is the difference between:

• Owning a product you can afford to keep alive and improving, or
• Being surprised by an endless stream of “unexpected” invoices and rewrites

The mindset shift: don’t just ask “How much is the MVP?”

A more useful set of questions to ask yourself (and any development partner):

• What will this MVP cost me to maintain for the next 2–3 years?
• How much should I budget per month for improvements after launch?
• What will hosting and infrastructure realistically look like at:
  • 100 users?
  • 1,000 users?
  • 10,000 users?
• How will we handle bugs, security updates, and incidents?
• Who is responsible for ongoing product discovery and prioritisation?

When you start from those questions, “How much is the MVP?” becomes just one line in a total cost of ownership conversation – not the whole story.

And that’s the point: MVP is your first 30–40%. The real game is whether you can sustainably fund and manage the remaining 60–70% required to turn that MVP into a SaaS business that grows instead of crumbling.

The anatomy of post-MVP SaaS development costs (1–3 year view)

Once the MVP is live, your budget stops being a one-off number and turns into a system: a mix of recurring and project-based costs that evolve as the product matures.

A useful way to think about this is in stages and buckets.

The three post-MVP stages (0–36 months)

You won’t move through these in a perfectly straight line, but they’re a good mental model:

1. Stabilisation (0–6 months after launch)

You’ve shipped. Now reality hits:

• Users are finding bugs you never saw in staging
• You’re patching security gaps and tightening up performance
• Onboarding is rough and support questions are piling up

Main focus: Keep the product stable enough that you’re not embarrassed to charge money.

Budget feel:

• Maintenance: high (lots of fixes)
• Infra: low–moderate
• New features: small, focused tweaks
• Support: scrappy but growing

2. Product-market fit search (6–18 months)

You have some paying customers or strong usage. Now you’re trying to prove this isn’t a fluke.

Main focus:

• Iterating on UX and features based on real feedback
• Improving activation, engagement, and retention
• Testing pricing and positioning
• Building the integrations your customers keep asking for

Budget feel:

• Maintenance: stabilising, but still necessary
• Infra: growing with usage
• New features: big slice of your spend
• Support & tooling: becoming more structured

3. Growth & scaling (18+ months)

You have traction. Now the work is about scale and efficiency:

• Handling more users, more data, more teams
• Making performance, reliability, and security “boring and predictable”
• Investing in features that move revenue and reduce churn
• Optimising internal workflows and support to protect margins

Budget feel:

• Maintenance: predictable, but more complex
• Infra: meaningful line item
• New features & experiments: still big, but more intentional
• Support & internal tools: increasingly important

The four big cost buckets after MVP

Across those stages, almost everything you’ll spend on your SaaS product fits into four buckets:

1. Maintenance & technical debt
2. Hosting, infrastructure & DevOps
3. Iterative improvements & new features
4. Support, customer success & tooling

Let’s break down what typically sits in each.

1. Maintenance & technical debt

This is the stuff you have to do to keep the product alive:

• Fixing bugs and production incidents
• Updating dependencies, libraries, frameworks
• Security updates and vulnerability patches
• Performance profiling and targeted fixes
• Handling breaking changes in third-party APIs

If your MVP was rushed or built without much architectural thinking, this also includes:

• Refactoring messy modules and critical flows
• Paying down shortcuts (e.g. “just put it in one big file for now”)
• Gradually replacing fragile parts before they cause outages

You can reduce maintenance costs over time with good engineering practices, but you never get them to zero.

2. Hosting, infrastructure & DevOps

This is what you pay so the software can actually run:

• Cloud hosting (servers/containers, databases, storage, CDN)
• Background workers and queues
• Monitoring, logging, and alerting tools
• Backups and disaster recovery
• Environment setup (dev, staging, production)
• DevOps / SRE time to keep all of this sane

Early on, infra might be a small number on your credit card. By the time you’re handling tens of thousands of users, infra can be a meaningful chunk of your monthly burn.

Architecture decisions made during MVP (e.g. multi-tenant vs single-tenant, heavy use of AI/ML services, need for multi-region) show up here as long-term costs.

3. Iterative improvements & new features

This is where the real upside lives.

Anything that moves the product forward beyond “keeping the lights on” sits here:

• Product discovery and prioritisation (product owner / PM work)
• UX research, wireframes, and UI design
• Implementing new features and improvements
• Reworking onboarding flows and key funnels
• Performance and usability improvements that boost conversion or retention
• A/B tests and experiments
• New platforms (e.g. adding mobile later)

This bucket usually takes the biggest share of your post-MVP budget if you’re serious about growth. If maintenance is the engine oil, this is the fuel that moves the car.

4. Support, customer success & tooling

Support isn’t just people answering emails. For SaaS, it’s also product and tooling work:

• Helpdesk systems and in-app chat
• Analytics and product analytics tools
• Error tracking and session replay
• Status pages, incident management tools
• Internal admin dashboards and support tools
• Self-service features that reduce ticket volume

Even if your support headcount is small, your development team will spend time on:

• Building better onboarding and self-service flows
• Creating internal tools so support doesn’t need engineers for everything
• Improving documentation and in-app guidance

This work doesn’t always look like “new features”, but it’s critical for scaling without drowning in tickets or churn.

How the mix shifts over 1–3 years

The exact numbers will vary by product, but a typical, healthy SaaS might see something like this distribution of post-MVP product budget:

These are rough percentages of your post-MVP product spend, not of your entire company budget.

Stage 1 — Stabilisation (0–6 months)

• Maintenance & tech debt: 35–45%
• Hosting & infra: 10–15%
• Iterative improvements: 25–35%
• Support & tooling: 10–20%

Most of your energy is spent fixing what reality reveals and making the product stable enough that new development isn’t constantly blocked.

Stage 2 — Product-market fit search (6–18 months)

• Maintenance & tech debt: 20–30%
• Hosting & infra: 10–20%
• Iterative improvements: 40–50%
• Support & tooling: 10–20%

You’re spending more on intentional improvements and experiments, still keeping maintenance under control, infra is growing but manageable.

Stage 3 — Growth & scaling (18+ months)

• Maintenance & tech debt: 20–25%
• Hosting & infra: 15–25%
• Iterative improvements: 35–45%
• Support & tooling: 15–25%

Here, infra and support/tooling usually become more significant, while iteration stays a big but more disciplined slice. Maintenance is still there but ideally predictable.

These aren’t budgets to copy-paste; they’re sanity checks. If you’re spending 70% of your product budget just fighting fires and almost nothing on iteration, that’s a red flag. If infra is tiny but users are complaining about speed and uptime, another red flag.

Turning this into actual planning

To move from “interesting framework” to “actual numbers” for your product, you can:

1. Start with your total product budget
   • “We can invest ~€X over the next 12–24 months into the product.”
2. Allocate high-level percentages by stage
   • Decide what phase you’re in (stabilisation, PMF search, or growth).
   • Use the ranges above to sketch a first-pass distribution.
3. Translate into monthly envelopes
   • Example: €240k over 24 months ≈ €10k/month on average.
   • Apply your chosen percentages to that monthly budget to see what’s realistic.
4. Map work to buckets
   • For each quarter: list planned initiatives and tag them as maintenance, infra, iteration, or support/tooling.
   • Check that your plan doesn’t silently push everything into “new features” while ignoring the rest.

A good development partner (in-house lead or an external team like VeryCreatives) should be able to co-create this split with you, based on your actual roadmap and risk profile, instead of just quoting a single build price.

Why this anatomy matters

Most budget surprises don’t come from the initial MVP number. They come from:

• Not realising how much of your future spend will be recurring, not one-off
• Underestimating the time and money needed for maintenance and infra
• Treating support and tooling as an afterthought instead of planned work
• Assuming “new features” will always be the majority, when in reality they’re just one of several necessary cost buckets

Once you see your post-MVP costs as a balanced portfolio across these buckets, you can:

• Have more honest conversations with co-founders and investors
• Evaluate offers from a custom software development company beyond just “day rates”
• Make trade-offs consciously (“We’ll spend less on new features this quarter to pay down technical debt,” etc.)

From here, we can zoom into each major bucket—starting with maintenance & technical debt—and talk about what to expect and how to keep those costs under control without starving your product of progress.

Maintenance & technical debt: keeping the lights on vs paying down the past

Once the MVP is live, not all work is glamorous. A big chunk of your budget goes into two very different kinds of effort:

• Maintenance – keeping the product healthy today
• Technical debt – fixing yesterday’s shortcuts so you don’t drown tomorrow

If you treat them as the same thing, you either overspend on “cleanup” or under-invest and end up in permanent crisis mode.

Let’s separate them properly and attach some realistic expectations:

What maintenance actually means in SaaS

Maintenance is the non-negotiable baseline of running a live product. It’s the work that keeps your product safe, usable, and trusted.

Typical maintenance work includes:

• Bug fixing & incident response
  • Reproducing and fixing user-reported issues
  • Handling production incidents (downtime, broken flows)
  • Writing tests to make sure bugs don’t come back
• Security & compliance updates
  • Patching vulnerabilities in frameworks and libraries
  • Updating dependencies to versions with security fixes
  • Adjusting to new compliance requirements (e.g. privacy changes)
• Performance & reliability care
  • Fixing slow endpoints and heavy queries
  • Ensuring background jobs don’t pile up
  • Improving error handling and retries
• Compatibility & ecosystem changes
  • Adapting to changes in third-party APIs (payments, email, auth, etc.)
  • Ensuring your app keeps working across browsers/devices

Some of this work is planned and some of it is reacting to things breaking in the wild. Either way, you will spend time and money on this. The question is how much and how predictably.

A simple way to budget for maintenance

You can fight over exact percentages, but for most early-stage SaaS products, a decent rule of thumb is:

Expect to invest 10–25% of your original MVP cost per year just to keep it healthy.

Example:

• MVP build budget: €80k
• Rough annual maintenance envelope: €8–20k/year

That might translate into:

• A small, steady trickle of maintenance tasks woven into your regular sprints, or
• A more formal maintenance retainer with your development partner (e.g. guaranteed hours per month for bug fixes, updates, and monitoring)

As your app grows more complex (more users, more features, more integrations), that percentage tends to go up, especially if you don’t invest in paying down technical debt.

Technical debt: the bill for past shortcuts

Technical debt isn’t just “bad code”. It’s:

Every shortcut you took in the past that makes work slower, riskier, or more expensive in the future.

These shortcuts are often intentional:

• “We’ll hardcode this for now; no time to make it configurable.”
• “Let’s put all this logic in one service so we can ship this week.”
• “We’ll worry about tests once we have users.”

And sometimes unintentional:

• The MVP was built by freelancers who left
• You leaned heavily on AI-generated code or copy-pasted snippets
• Early architecture decisions don’t fit where the product is going

Technical debt shows up as:

• Slower development (“this small change takes weeks because everything is tangled”)
• Fragility (new features break unrelated parts)
• Increasing bugs and production incidents
• Developers telling you “we need to refactor this” more and more often

Maintenance keeps the house standing. Technical debt is the fact that some walls are crooked and the wiring is from 1983.

How to tell if you have a maintenance problem vs a debt problem

You mostly have a maintenance problem if:

• Most bugs are simple, localised issues
• New features are reasonably quick to build
• Your team can estimate work with decent accuracy
• Incidents happen, but they’re manageable and not catastrophic

In this case, you probably just need:

• A clear maintenance plan (e.g. reserved time every sprint, or a support/maintenance retainer)
• Decent monitoring and logging
• Time set aside for routine updates

You have a serious technical debt problem if:

• Every feature takes much longer than you expect
• Developers frequently say “we need to rewrite this part first”
• You’re afraid to touch certain areas of the code
• Fixing one bug tends to create two new ones
• You’ve had a few scary outages tied to old decisions

In that case, the solution is not “more maintenance”. It’s a structured debt reduction plan: audits, refactors, and sometimes partial rebuilds.

What a technical audit and cleanup usually looks like

When a serious team (in-house lead or a custom software development company) takes over a messy MVP, they’ll usually:

1. Audit the codebase and architecture
   • Code quality review
   • Dependency, security, and performance checks
   • Mapping of particularly risky / fragile areas
2. Prioritise the biggest risks and bottlenecks
   • Modules that block future features
   • Parts of the system causing outages or major bugs
   • Areas that are impossible to test or reason about
3. Plan refactors in safe iterations
   • Break big rewrites into manageable steps
   • Add tests around critical flows before changing them
   • Improve observability (logging, metrics) so you can see impact
4. Run cleanup in parallel with business priorities
   • Combine refactor work with feature work where possible
   • Avoid “freeze all new work for 6 months while we rewrite everything” unless absolutely necessary

Debt cleanup isn’t one project you “finish”. It’s a habit that reduces risk and keeps velocity from crashing.

Attaching rough numbers: how big can the debt bill get?

Every product is different, but here’s a reasonable mental scale:

Debt level	Typical situation	Cleanup cost as % of original MVP	Example cost (for illustration)	Notes
Low debt, well-built MVP	Some rough edges, but overall decent architecture and tests; codebase is understandable and extendable	Small extra budget beyond normal maintenance (often folded into regular sprints)	If MVP was €80k, additional structured “debt work” might be relatively minor and spread across normal iterations	Debt tasks can usually be tackled alongside feature work without separate big projects
Medium debt, typical rushed MVP	Built fast by a small team or freelancers; limited tests; shortcuts in key areas	~20–50% of original MVP cost over ~12–18 months	MVP cost €80k → expect €16–40k of deliberate cleanup/refactor work	Needs a planned cleanup roadmap, but a rewrite usually isn’t necessary if managed well
High debt, “vibe-coded” or AI-patched MVP	No tests, tangled logic, fragile infrastructure; new features are painful; bugs frequent; outages likely	~50–100% of original MVP cost over ~12–24 months (or more if a rebuild is needed)	MVP cost €60k → debt work might be €30–60k+ over 1–2 years	At this level, a partial or full rebuild may be more cost-effective than endless patching; a proper audit is essential

The important point: ignoring this doesn’t make it cheaper. It just means you pay for it in slow progress, higher risk, and developer churn.

How to structure maintenance and debt work in your roadmap

A practical way to avoid chaos is to treat maintenance and debt as first-class citizens in the roadmap, not “whatever’s left over”.

Some workable patterns:

1. Reserve capacity in every sprint
   • e.g. 20–30% of engineering time is always for maintenance, updates, and targeted refactors.
   • The rest goes to new features and experiments.
2. Create a visible maintenance/debt backlog
   • Track issues in the same tool as feature work.
   • Rank them by impact on stability, speed, and future features.
3. Run occasional “stability or performance” cycles
   • Every X sprints, dedicate most of the time to cleanup and hardening.
   • Communicate this clearly internally: “We’re investing in going faster later.”
4. Tie debt tasks to business goals
   • “Refactor this module → allow us to launch feature X 2x faster.”
   • “Improve architecture here → reduce monthly incident volume by Y%.”

Your goal isn’t a perfectly clean codebase. It’s a codebase that lets you move safely and quickly.

Where an ongoing maintenance partnership fits in

If you’re working with an external partner instead of a full in-house team, you don’t want “call us when something’s on fire” as your only arrangement.

A healthier structure often looks like:

• Essential maintenance layer
  • Fixed monthly retainer covering:
    • Bug fixing and small patches
    • Security and dependency updates
    • Basic performance tweaks
    • Monitoring and incident response
  • Gives you predictable cost and response times
• Planned debt reduction & improvement work
  • Separate, planned work streams or mini-projects
  • Linked to your roadmap: “clean this up so we can do that”
  • Budgeted as part of your iterative improvements, not ad-hoc panic

This is roughly the spirit of how a serious SaaS-focused agency (like VeryCreatives) treats post-MVP care: not as random support tickets, but as a structured, predictable layer under your product roadmap.

Treat maintenance and debt as investments, not distractions

It’s very tempting to see maintenance and refactoring as things that “get in the way” of new features. But for a SaaS business, they’re what allow you to:

• Ship features faster and with fewer surprises
• Sleep better when you have paying customers in production
• Avoid huge, disruptive rewrites later
• Keep developers and partners happy (nobody loves working in a minefield)

So instead of asking:

“How do we spend as little as possible on maintenance and cleanup?”

A better question is:

“What’s the minimum disciplined investment we need to keep this product safe, fast, and easy to improve?”

Once you frame it that way, it becomes much easier to budget a realistic percentage of your post-MVP spend for keeping the lights on today and paying down the past just enough to keep your future open.

Hosting, infrastructure & DevOps: what you’ll actually pay the cloud providers

For a lot of non-technical founders, “the cloud” feels like a magical flat fee. In reality, it’s a meter that you control with your product decisions.

Good news: early on, infra doesn’t have to be huge.

Bad news: ignore it, and you’ll either overpay quietly or get burned when you hit traction.

Let’s break down what you’re actually paying for and how to think about these costs over the first 1–3 years:

What “infrastructure” actually includes

When you pay AWS/Azure/GCP (or similar), you’re usually paying for some combination of:

• Compute
  • Servers / containers (EC2, ECS, Kubernetes, App Service, etc.)
  • Background workers and scheduled jobs
• Data & storage
  • Databases (Postgres, MySQL, Mongo, etc.)
  • Caches (Redis, Memcached)
  • File storage (S3/Blob storage – for images, documents, exports)
  • Backups and snapshots
• Networking & delivery
  • Load balancers, API gateways
  • Content Delivery Network (CDN) for assets and static content
• Monitoring & observability
  • Logs, metrics, traces
  • Error tracking (e.g. Sentry)
  • APM tools
• Security & identity add-ons
  • WAF (web application firewall)
  • Key management, secrets storage
  • VPN or bastion hosts for secure internal access

On top of that, you may have third-party hosted services, such as:

• Managed search (e.g. Algolia)
• Email / SMS providers
• Payment providers
• AI/ML APIs (e.g. OpenAI, image processing, etc.)

Each of these is relatively small on its own. Together, they form your monthly infra bill.

You don’t just have “one server” – environments matter

Most serious SaaS setups have at least:

• Development – where engineers test locally and in shared dev environments
• Staging – a pre-production environment to test integrated changes
• Production – what paying customers use

Why this matters for cost:

• Staging often mirrors parts of production (smaller but similar), so you’re paying some fraction of prod twice.
• Dev environments might use on-demand or small instances, but they still add up.
• You may later add preview environments (temporary per-feature environments) that incur extra cost but improve quality.

A very early-stage product might keep dev/staging tiny and production modest. As you scale, you’ll often duplicate parts of your stack across environments for safety.

The main cost drivers founders should care about

You don’t need to know every AWS service by name. You do need to understand what moves the needle:

1. Usage volume
   • More users → more requests → more compute, more DB reads/writes, more storage.
2. Data intensity
   • Heavy analytics, event tracking, file uploads, or large datasets push storage and compute costs up.
3. Performance & availability goals
   • Highly available setups (multi-region, automatic failover, strict SLAs) cost more than “good enough” uptime for early-stage products.
4. Architecture choices
   • Multi-tenant vs single-tenant (e.g. per-customer databases).
   • Microservices vs a simpler monolith.
   • Heavy real-time features (websockets, live dashboards, etc.).
5. AI/ML / heavy compute
   • Using big language models, image processing, or complex data crunching can add a separate and substantial bill.

Good DevOps engineering is about tuning these levers to match your stage, not overbuilding or running everything on one overloaded machine.

Rough infra cost tiers for early SaaS

These are deliberately broad, but they’re useful sanity checks.

1. Early beta / pre-PMF (tens to low hundreds of active users)

• Simple monolith app, single region
• Modest database, limited background processing
• Minimal monitoring

Typical monthly range:

• €100–€500 / month for core infra
• Plus small amounts for things like email, error tracking, etc.

Here, the risk isn’t “this is too expensive”. The risk is under-investing in observability and not knowing what’s happening when things go wrong.

2. Early traction (hundreds to low thousands of active users)

• App is still relatively simple, but volume is up
• You now care about uptime and performance
• You’re adding more environments, better monitoring, backups

Typical monthly range:

• €500–€2,000+ / month for infra
• More if you’re data-heavy or have lots of real-time features

This is where architectural shortcuts begin to show. If the MVP was designed with no thought for scale, small increases in traffic can cause outsized pain and forced rework.

3. Growing & scaling (thousands to tens of thousands of active users)

• Multiple services, more complex data flows
• Higher expectations on performance & availability
• More integrations, scheduled tasks, and storage

Typical monthly range:

• €2,000–€10,000+ / month (or more for very data/AI-heavy systems)

At this point, infra is a meaningful line in your P&L. Smart optimisation work can save thousands per month; sloppy decisions can quietly burn the same amount.

Where DevOps/SRE fits into your budget

Infra cost isn’t just what you pay cloud providers. It’s also what you pay people (or partners) to manage and optimize all this.

Good DevOps / SRE work helps you:

• Set up sensible defaults (backups, autoscaling, logging, alerts)
• Avoid catastrophic failures (no backups, single points of failure)
• Keep infra costs under control (right-size instances, turn off unused resources)
• Deploy frequently without breaking things (CI/CD pipelines)

If nobody is thinking about this, you tend to get one of two bad outcomes:

• Overspend quietly
  • Over-provisioned resources “just in case”
  • Old environments left running forever
  • Multiple tools doing the same job
• Run too “hot” and fragile
  • No backups or disaster recovery
  • Manual, risky deployments
  • Outages that take hours to debug because logging is terrible

Depending on your setup, DevOps can be:

• A part-time responsibility of a senior engineer early on
• A dedicated role or a specialised part of your external team as you grow
• A service bundled into a retainer with a custom software development company (common for small/mid SaaS teams)

How architecture and “nice-to-haves” impact cost

Some examples of decisions that sound purely technical but have budget implications:

• Multi-tenant vs single-tenant
  • Single-tenant (e.g. separate DB per customer) can make sales to larger clients easier but often costs more infra-wise.
  • Multi-tenant can be more efficient and cheaper at scale but requires careful design.
• Microservices vs monolith
  • Microservices give more flexibility at high scale but come with more infra overhead, more services, more points of failure.
  • For most early-stage products, a well-structured monolith is cheaper and easier to operate.
• Real-time everything
  • Live dashboards, notifications, and collaborative editing can be infra-hungry.
  • Sometimes you can fake “real-time” with smart polling or partial updates to keep costs and complexity down early.
• AI/ML features
  • Calling external AI APIs or running your own models can add a per-request cost that scales with user activity.
  • Often worth it, but you need to track and budget for it explicitly.

This is where a SaaS-savvy engineering partner earns their keep: not just building the feature, but choosing an approach that won’t explode your cloud bill in 18 months.

Infra costs vs developer time: both count

A common trap: trying to minimise cloud bills at the expense of developer time.

Example:

• You can save €200/month on infra by using a very manual, fragile setup that takes your team 10 extra hours each month to babysit.
• At reasonable developer day rates, those 10 hours are more expensive than the infra you “saved”.

On the flip side:

• You can easily burn an extra €1–2k/month on over-provisioned resources and unused tools if no one’s watching.

The point: treat infra euros and engineering hours as part of the same budget. DevOps is partly about finding the right trade-off for your stage.

How a good partner helps you here

Whether it’s an internal tech lead or an external custom software development company, the right partner should:

• Explain your current infra setup in founder-friendly language
• Give you ballpark cost projections for realistic usage scenarios
• Suggest simple, robust architectures at MVP stage (not “Kubernetes for five beta users”)
• Build monitoring and backups in from day one
• Periodically review and right-size infra as you grow

For many non-technical founders, this is one of the most valuable aspects of a long-term relationship with a team like VeryCreatives: you’re not just renting code, you’re renting judgment about where to spend and where to save on the cloud side.

From “mystery AWS bill” to planned line item

Instead of treating hosting and infra as that scary line that appears on your credit card each month, bake it into your planning:

• Assume a small but growing infra budget from day one
• Tie infra decisions to business stage and revenue, not “we like cool tech”
• Make someone explicitly responsible for monitoring and optimizing these costs
• Revisit your setup at key milestones (post-MVP, after first big customer, before major growth push)

Do that, and “what you pay the cloud providers” becomes predictable and intentional – just another part of your post-MVP SaaS development costs, not an unpleasant surprise.

Iterative improvements: budgeting for actual progress, not just firefighting

If maintenance and infrastructure are about not going backwards, iterative improvements are about actually moving forwards.

This is the part of your budget that turns a functional app into a product that wins: better onboarding, smoother flows, features that customers rave about, experiments that increase revenue.

And yet, in many early-stage SaaS teams, this work constantly gets eaten by:

• “One more urgent bug”
• “Just this quick integration”
• “We’ll improve onboarding later”

Let’s make sure you actually budget for progress – not just survival:

Why you must keep building after MVP

An MVP that doesn’t evolve will almost always lose, even if it was “perfect” at launch.

After your first release you’ll discover:

• Users don’t behave exactly as you assumed
• Some “must-have” features barely get touched
• Some “small” edge cases are actually core workflows
• The market shifts, competitors change, new expectations appear

If you don’t have time + budget earmarked for iteration, you end up with:

• A product that feels “stuck” while competitors ship improvements
• Slow responses to customer feedback
• Higher churn because onboarding and UX never get better
• A demotivated team stuck in pure maintenance mode

Iteration isn’t a luxury – it’s how you buy your way to product-market fit and beyond.

What iterative work actually looks like

“New features” is only part of it. Iterative improvement usually includes:

• Product discovery & strategy
  • Talking to users, analysing usage data
  • Prioritising what to build next based on impact
  • Saying “no” to features that don’t move the needle
• UX & UI improvements
  • Clarifying confusing screens and flows
  • Improving empty states, error messages, and microcopy
  • Streamlining onboarding, reducing friction in signup and activation
• New features & enhancements
  • Shipping entirely new capabilities your customers need
  • Deepening existing features to fit real workflows
  • Adding integrations that unlock deals or stickiness
• Experiments & optimisation
  • A/B tests for key flows (signup, pricing, upgrade paths)
  • Iterating on plans, trial lengths, and packaging
  • Testing different onboarding paths or nudges

This is the work that connects directly to metrics like activation, retention, expansion revenue, and referrals.

Budget models for iterative development

You basically have three ways to structure this work, whether with an in-house team or a partner.

1. Time & materials (T&M)

You pay for the actual hours a team spends on your product.

Good for:

• Early stage, when discovery and priorities change quickly
• Flexible roadmaps with changing requirements
• Short-term bursts of work

Less good for:

• Predictable monthly spend (it can fluctuate)
• Teams that struggle with scope creep / constant re-prioritisation

2. Fixed-scope projects

You define a clear scope (“build feature X”) and get a fixed price and timeline.

Good for:

• Well-defined features with stable requirements
• Founders who need strict budget caps per project

Less good for:

• Fast iteration and experimentation
• Continuous product evolution (too much overhead specifying every small change)

3. Retainer / dedicated “Growth Team”

You agree a stable monthly investment in a cross-functional team (e.g. designer + 1–3 devs + QA + PM), focused on a continuous roadmap.

Good for:

• Predictable monthly SaaS development costs
• Continuous, compound improvements across UX, infra, and features
• Treating your partner like a semi-internal product team

Less good for:

• Very sporadic work (long pauses, no clear roadmap)
• Founders who just want one-off features, not ongoing collaboration

For non-technical founders, that “Growth Team” structure often works best: you know roughly what you’re spending each month and can tie it directly to roadmap outcomes.

How much should you actually invest in iteration?

Exact numbers vary, but as a starting point:

• In a healthy, growing SaaS, iterative improvements often take 40–50%+ of your post-MVP product budget
• If iteration drops below ~25% for long periods, you’re likely stagnating or stuck in permanent firefighting

Example with round numbers:

• Total monthly product budget (dev, design, product, excluding marketing): €20k
  • Maintenance & technical debt: €4–6k (20–30%)
  • Hosting & infra: €2–4k (10–20%)
  • Iterative improvements: €8–10k (40–50%)
  • Support & tooling-related dev: €2–4k (10–20%)

You can’t copy-paste this, but you can use it as a sanity check:

• If everything goes to maintenance and support, you’re stuck
• If nothing goes to maintenance and infra, you’re building on sand

From wishlist to roadmap: making iteration real

Most founders have a massive feature wishlist. The trick is converting that into a roadmap that fits your budget.

A practical approach:

1. Define your primary goals for the next 3–6 months
   • e.g. “Increase trial-to-paid conversion”, “Improve activation”, “Reduce churn in month 2”.
2. Map potential initiatives to those goals
   • Onboarding improvements → activation
   • Key integration → sales velocity
   • Performance work on a critical workflow → reduced churn / increased usage
3. Estimate & prioritise ruthlessly
   • Small, high-impact changes first (“1–2 week wins”)
   • Defer “cool but fuzzy” big features
4. Ring-fence iteration time
   • Decide up front: “We will spend at least X% of our monthly capacity on roadmap-led improvements.”
   • Treat that as non-negotiable, just like rent or salaries.

A good product team or partner will keep coming back to: “What are we trying to move, and is this the best next step?” rather than, “What random feature did someone ask for last week?”

Example team shapes & what they can achieve

To make this concrete, here are rough examples of what different monthly budgets might buy in terms of iterative capacity (numbers illustrative):

Lean iteration setup

• ~1 full-time developer equivalent
• Part-time designer
• Some product support from founder / fractional PM

Budget: maybe €8–12k/month (depending on rates/location)

Realistic outcomes:

• 1–2 meaningful releases per month
• Regular UX polish and small features
• Some maintenance folded into the same team

Dedicated growth squad

• 2–3 developers (mix of frontend/backend)
• 1 UX/UI designer
• 1 QA (part-time or full)
• 1 product manager / product owner

Budget: maybe €20–40k/month (again, ballpark)

Realistic outcomes:

• Frequent, smaller releases (weekly or bi-weekly)
• Parallel work on multiple areas (onboarding + feature X + performance)
• Structured experiments and continuous discovery
• Maintenance, tech debt, and infra all properly handled alongside new work

This is roughly what a dedicated growth team from a custom software development company looks like – you’re not buying “hours”, you’re buying a steady flow of product improvements.

Balancing iteration with maintenance: avoiding the two extremes

Two traps to watch out for:

1. All new features, no foundations
   • You push your team to ship feature after feature.
   • Maintenance, security, and infra are afterthoughts.
   • Eventually, everything slows down and breaks more often.
2. All firefighting, no progress
   • You never commit to goals or a forward roadmap.
   • Every sprint is dominated by urgent bugs and “quick fixes”.
   • After a year, the product doesn’t feel meaningfully better.

Healthy teams and good partners explicitly balance:

• A baseline of maintenance + infra work
• A protected slice for roadmap-led, goal-driven iteration

If you’re working with an agency like VeryCreatives, that might look like:

• A maintenance/ops layer that quietly keeps things safe and updated
• A dedicated iteration layer (growth team) focused on delivering business outcomes each sprint

Progress is a line item, not leftovers

Instead of asking:

“What can we squeeze in after we fix all the bugs?”

Flip it to:

“How much are we going to invest every month in making the product better, and how do we get the best return from that?”

When iterative improvements are:

• Budgeted,
• Goal-linked, and
• Owned by a cross-functional team (design, dev, product),

you stop feeling like you’re just “keeping up” and start feeling like you’re actually building a product that gets more valuable every quarter.

Support, customer success & internal tooling: the “hidden” development costs

When founders think about “SaaS development costs”, they usually picture features users can click on.

But a surprising amount of your real development budget ends up in things your customers never see directly:

• Internal dashboards
• Admin tools
• Support workflows
• Customer success automation
• Analytics and reporting setups

These don’t sit in your marketing screenshots, but they’re essential if you want a business that doesn’t collapse under its own weight.

Let’s unpack where these “hidden” costs come from and how to plan for them:

Why support and success belong in your development budget

Support and customer success aren’t just people answering emails and jumping on calls. In SaaS, they are tightly linked to product and engineering:

• If onboarding is confusing → more tickets.
• If customers can’t self-serve basic actions → more tickets.
• If you can’t see what a user did before an issue → longer ticket handling.
• If there’s no internal tooling → every small admin task needs a developer.

Every time your team thinks “We’ll just ask a developer to run a script” or “We’ll export this manually from the database”, you’re spending engineering hours on support tasks instead of product improvement.

So part of your post-MVP development cost is actually:

Building the tools and features that let support and customer success do their job without constantly pulling engineers in.

The tooling stack you’ll eventually pay for

Tools vary by stack and stage, but most SaaS products end up with some mix of:

• Helpdesk & communication
  • Zendesk, Intercom, Help Scout, Front, etc.
  • Live chat, in-app messaging, email support
• Knowledge & education
  • Public help center / docs tools
  • In-app guides, product tours, and checklists
• Analytics & product analytics
  • Mixpanel, Amplitude, PostHog, or similar
  • Event tracking and funnel analysis
• Error tracking & debugging
  • Sentry, LogRocket, Datadog, etc.
  • Session replay tools
• CRM & billing
  • HubSpot, Pipedrive, Salesforce, or Stripe + add-ons
  • Subscription management and dunning processes

These usually come with per-seat or usage-based pricing, but there’s a second cost people forget:

Someone has to integrate them, wire them into your product, and keep them working.

That “someone” is a developer and/or product engineer – which means these tools also belong in your development cost conversation.

Internal tools: the invisible time-saver (or time sink)

At first, you’ll probably do everything manually:

• Manually upgrading/downgrading accounts in the database
• Manually issuing refunds
• Manually fixing user data
• Asking a dev to run “just one little script”

That works for your first 5–10 customers. It does not scale.

Eventually, you’ll need internal tooling, such as:

• Admin panels
  • View and edit user accounts, permissions, and usage
  • Impersonate a user to see what they see
  • Manage subscriptions, credits, features flags
• Operational dashboards
  • Overview of key metrics (signups, churn, errors, payments)
  • Backlog of tasks that support/success need to act on
• One-click actions
  • Resend invitations, reset things, clear queues
  • Bulk operations on users or resources

You can hack this together with off-the-shelf tools, but some level of custom internal tooling is nearly always needed – and that’s development time that doesn’t directly “show” in the product UI.

How these “hidden” costs creep into your roadmap

Typical pattern in early SaaS:

1. MVP live – everyone focused on new features
   • Support handled directly by founders
   • Manual fixes in the database
   • No real internal tools, just raw queries
2. Customer count grows – pain appears
   • Support tickets increase
   • Founder time sinks into “Can you check this account?”
   • Developers context-switch constantly to run small fixes
3. Pressure builds
   • Support complains they can’t help users without devs
   • Devs complain they can’t ship features because of constant interruptions
   • Founders experience that everything feels slow and fragile

At this stage, the realisation hits: you need to allocate deliberate development time to:

• Better onboarding and self-service features
• Internal admin tools
• Integration and optimisation of support/success tooling

If you don’t, you’ll burn both your team and your users.

Budgeting for support & tooling-related development

As a rough mental model, for a growing SaaS (beyond a handful of customers), it’s realistic that 10–20% of your product development capacity will be tied to support, success, and internal tooling work.

That might include:

• Building and refining an admin panel
• Adding “view as user” / impersonation features
• Improving error messages and support context
• Wiring in new helpdesk or analytics tools
• Creating self-service flows (cancelation, plan changes, data export, etc.)
• Making dashboards for your success team to watch key accounts

The number will fluctuate month to month, but if it’s consistently close to 0%, you’re probably:

• Underinvesting in efficiency
• Over-relying on engineers as manual operators
• Quietly increasing your operational risk and costs

How smart product work reduces support costs

Not all “support-related” work is ticket-driven. Some of the best investments are proactive UX and product changes that reduce ticket volume and make customers happier.

Examples:

• Improved onboarding flows
  • Clearer first-run experiences
  • Tooltips, checklists, and progress tracking
  • In-product education instead of docs nobody reads
• Better error states & recovery
  • Helpful messages that explain what went wrong and what to do
  • Retry / undo options
  • Links to relevant help articles
• Self-service account management
  • Let users change email, company details, and team members themselves
  • Manage subscriptions, invoices, and usage self-serve
  • Export data without opening a ticket
• Customer health visibility
  • Dashboards for success teams showing usage changes, at-risk accounts
  • Triggers for proactive outreach instead of reactive rescue

These things cost dev and design time, but they pay off by:

• Reducing ticket volume
• Shortening resolution time
• Increasing customer satisfaction and retention
• Freeing up engineers to work on higher-impact features

Early-stage vs later-stage: how the needs evolve

Stage	Rough customer count	Who handles support	Tooling situation	Typical dev tasks
Early stage (MVP → first customers)	First users / first few customers	Mostly founders (sometimes 1 generalist)	Very lightweight: shared inbox, simple help docs, maybe basic chat tool; minimal or no internal tools, lots of manual work	- Basic error tracking setup - Very simple/bare-bones admin panel - Initial helpdesk integration - Quick fixes to unblock early users
Growing stage (dozens → hundreds of customers)	Dozens to low hundreds of paying/active customers	Dedicated support / customer success roles start to appear	Support tools now essential; internal tools becoming critical to handle volume; more structured help center & ticketing	- Build a proper admin panel - Better logging & analytics for support - Onboarding and self-service improvements - Integrations with more specialised tools (helpdesk, analytics, CRM)
Scaling stage (hundreds → thousands of customers)	Hundreds to thousands of customers / multiple segments	Support & success are teams with defined processes and KPIs	Tooling and automation are critical: robust internal tools, role-based access, audit logs, complex workflows	- Advanced internal tools & dashboards - Workflows spanning multiple systems (billing, CRM, support, product) - Deeper analytics, segmentation, and health scoring - Automation to reduce manual intervention and repetitive support tasks

At each stage, the fraction of your dev budget for support/success and tooling can stay similar – but the absolute spend grows with complexity and customer count.

Working with a partner on these “unsexy” pieces

Many founders feel weird about asking an external dev team to work on “boring” admin and support tools.

But for a serious SaaS-focused partner, this is exactly the kind of work that:

• Makes your business more scalable and less fragile
• Directly improves your ability to serve and retain customers
• Frees up founder and support time

A good custom software development company won’t just say, “Sure, we’ll build whatever admin panel you want.” They’ll also ask:

• Who will use this internally and how often?
• What tasks are currently bottlenecked on developers?
• Which support problems show up repeatedly that we can design out of the product?

Teams like VeryCreatives can combine:

• UX thinking (how to make this usable for your internal team)
• Engineering (building the tools securely and efficiently)
• Product sense (prioritising what internal tools actually matter now)

Internal work is product work

It’s easy to think:

“This doesn’t face customers, let’s do it later.”

But internal tooling, support integration, and customer success enablement are product work, because they:

• Decide how quickly and smoothly users get help
• Decide whether your team can handle growth without breaking
• Decide how much of your dev budget goes to firefighting vs building

So when you think about SaaS development costs, don’t just list user-facing features and hosting. Include a line for:

• Support & success enablement
• Internal tools and admin
• Integrations that make your team more effective

Plan for those explicitly, and they stop being “hidden costs” and start being strategic investments in a product – and a company – that can actually scale.

Web, mobile, or both? How platform decisions shape your SaaS development costs

One of the biggest early decisions you’ll make is where your SaaS lives:

• Just in a browser (web app)?
• Native mobile apps as well (iOS, Android)?
• Cross-platform (one codebase, multiple platforms)?

This isn’t just a design decision – it’s a cost structure decision that affects both your MVP and everything that comes after.

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Step 1: Do you actually need mobile from day one?

Not every SaaS needs a mobile app at launch.

You probably don’t need mobile at MVP if:

• Your users mostly work at a desk (think B2B tools, internal systems).
• The core value happens in longer sessions (analytics dashboards, complex workflows).
• You’re still testing basic positioning and features.

You might need mobile early (or at least soon after MVP) if:

• Your product is used “on the go” (field work, logistics, events, sales in the field).
• Your users expect quick, frequent check-ins (notifications, approvals, quick actions).
• Competitors already offer mobile and it’s part of the buying decision.

A common smart path:

Start with a strong web app (responsive, works on mobile browsers), then invest in mobile once you see clear product-market fit and usage patterns.

That lets you validate demand before committing to the extra ongoing cost of mobile.

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The main platform options (and what they mean for costs)

You basically have four “layers” to choose from:

1. Responsive web app (no native mobile)
2. Cross-platform mobile (React Native, Flutter, etc.)
3. Full native apps (iOS + Android)
4. Hybrid approach (web + limited mobile companion)

Let’s look at them through a cost lens:

1. Web-only (responsive web app)

You build a single web application that works on desktop and mobile browsers.

Pros:

• One codebase = simpler architecture and lower dev/maintenance costs.
• Faster to ship and iterate.
• No app store reviews, approvals, or OS-specific issues.

Cons:

• Limited access to device features (push notifications, offline, deep OS integration).
• Mobile UX might never feel as “native” or smooth as a real app.
• Some users will always ask, “Do you have an app?”

Cost perspective:

• Lowest upfront and ongoing development cost.
• Best option if you’re still proving the concept.
• You still need to invest in good responsive design and mobile UX, not just “it loads on a phone”.

2. Cross-platform mobile apps (React Native, Flutter, etc.)

You keep a web app but also build a cross-platform mobile app where one codebase runs (with some platform-specific tweaks) on both iOS and Android.

Pros:

• Single mobile codebase, two platforms.
• Faster than building and maintaining fully separate native apps.
• Good access to device features and app-store presence.

Cons:

• More complex development & testing than web-only.
• Still some platform quirks – you don’t get “free” perfection on both iOS and Android.
• You now have at least two main surfaces to maintain (web + mobile).

Cost perspective:

• Upfront cost clearly higher than web-only.
• Ongoing cost: every feature may require web + mobile implementation and testing.
• Good middle ground for many SaaS products that genuinely need mobile presence but don’t need hardcore native performance.

3. Fully native apps (separate iOS + Android)

You build separate apps for iOS and Android, plus your web app.

Pros:

• Best possible native feel, performance, and access to platform features.
• Can be a differentiator in consumer products or where UX is everything.
• Sometimes required for specific device capabilities.

Cons:

• Three major surfaces to maintain (web, iOS, Android).
• You likely need different specialists (or a bigger team) for each.
• More complex release & testing processes.

Cost perspective:

• Highest upfront development cost.
• Highest ongoing maintenance and iteration cost: every change may need 3 implementations and 3 test passes.
• Rarely justified at MVP stage unless the entire product is inherently mobile-first and UX-sensitive (e.g. fitness apps, consumer social, etc.).

4. Hybrid / companion approach

You build:

• A full-featured web app, and
• A slimmer mobile app focused on a subset of workflows (e.g. notifications, approvals, quick edits).

This can be either cross-platform or native, but intentionally smaller in scope than the web app.

Pros:

• Keeps most complexity on the web side.
• Mobile app stays lean and focused on high-frequency tasks.
• Reduces mobile dev load compared to full feature parity.

Cons:

• Some advanced tasks require switching to the web.
• UX needs to clearly communicate “mobile is for X; web is for everything else.”

Cost perspective:

• More expensive than web-only, cheaper than fully equal web + mobile parity.
• A good compromise for B2B SaaS that need “check in on the go” more than full mobile workflows.

How platform decisions affect post-MVP costs

Adding mobile doesn’t just affect your MVP budget. It changes your monthly cost structure:

1. Development & maintenance load
   • Bugs now appear on 3 platforms instead of 1.
   • OS updates (iOS/Android) create regular work, independent of your roadmap.
   • Testing time increases with each release (more devices, more flows).
2. Release & coordination overhead
   • Every roadmap item might need: web implementation + mobile implementation + backend changes.
   • You coordinate app store releases and reviews along with web deployments.
3. Design & product complexity
   • Designers consider multiple breakpoints and interaction patterns.
   • Product has to decide which features are mobile-friendly and how they behave across platforms.
4. Team composition
   • You may need: web engineers + mobile engineers (or cross-platform specialists) + QA who know both.
   • If you rely on outsourced mobile app development, you need good coordination between web and mobile vendors — or a single partner who does both well.

This is why platform strategy is a cost decision as much as a UX decision.

Outsourced mobile app development: when it helps and where it bites

Bringing in an external team for mobile can be a smart move, especially early on:

Advantages:

• Access to experienced mobile engineers without hiring full-time.
• Faster initial delivery if your core team is web-focused.
• Clear scope: “Here is the mobile app we need for the next 6–12 months.”

Risks if not managed well:

• Fragmentation: one team builds web, another builds mobile, no one owns the full product experience.
• Inconsistent UX and behaviours across platforms.
• Harder coordination of releases and bug fixing.

To make outsourced mobile app development work, you need:

• A shared roadmap across web and mobile.
• Clear contracts around ongoing maintenance (not just “we’ll build v1 and disappear”).
• A strong product owner (internal or at your custom software development company) who balances priorities across platforms.

This is where a partner who handles both web and mobile as one product (rather than disconnected projects) can save a lot of pain and money.

A realistic roadmap: when to add mobile

Here’s a common, sensible path for many SaaS founders:

Phase 1 – Web-first MVP

• Build a robust web app with good responsive design.
• Ensure key workflows are usable on a mobile browser (even if not perfect).
• Focus budget on learning, getting users, and proving value.

Phase 2 – Signal-based decision

Once you have real usage:

• Look at how many users access your site via mobile browser.
• Talk to customers: do they need native features (push notifications, offline, camera, etc.)?
• Check how often “We need an app” comes up in deals you care about.

If you see consistent need and clear upside, then you commit to mobile.

Phase 3 – Mobile companion app (outsourced or in-house)

• Start with a focused mobile scope: notifications, quick actions, essential workflows.
• Use cross-platform tech if it fits your stack and team.
• Align mobile work tightly with web roadmap (shared backlog, shared design system).

Phase 4 – Deepening mobile as you scale

• Add more complex features to mobile once core flows and product strategy are stable.
• Consider whether mobile can be a differentiator (e.g. best-in-class UX for field teams).
• Treat mobile as a first-class citizen in planning and budgeting.

This staged approach keeps your SaaS development costs under control while still leaving room to build strong mobile experiences when they actually matter.

Platforms are levers, not checkboxes

Instead of asking:

“Do we need an app? Yes/No.”

Try asking:

• Which jobs to be done really need mobile?
• What’s the smallest, most valuable mobile experience we could offer?
• How does each platform choice change:
  • Our initial build cost?
  • Our monthly maintenance cost?
  • Our team/partner requirements?

When you treat web vs mobile as strategic levers, not checkboxes, you can design a product roadmap – and a cost structure – that fits your stage now and leaves room to grow into “both” when the business is ready.

Choosing a custom software development company & engagement model that won’t wreck your budget

By this point, it’s probably clear: you’re not just buying an MVP. You’re buying into a multi-year relationship with whoever builds and evolves your product.

Choose badly, and you get:

• A shiny MVP that’s impossible to extend
• Surprise invoices, constant rewrites, and a mystery AWS bill
• A team that ships features, but not outcomes

Choose well, and you get:

• A product that can actually grow
• Predictable costs
• A partner who helps you say “no” as often as “yes”

Let’s break down how to pick that partner and set up an engagement model that doesn’t blow up your budget later:

First decision: freelancers, in-house, or a custom software development company?

You’re usually comparing four options:

1. Solo freelancers / small freelance network
2. In-house team
3. Generic agency
4. SaaS-focused custom software development company

There’s no one right answer, but there is a right answer for your stage and risk tolerance.

1. Freelancers / small contractor network

Pros:

• Low apparent cost, flexible
• Easy to start quickly
• Good for very narrow, well-defined tasks

Cons:

• Hard to get a cohesive product (UX, frontend, backend, infra, QA)
• Knowledge sits in individual heads, not a team
• Higher risk of churn (people leaving mid-project)
• You become the de facto PM/CTO

Best for: very early experiments, prototypes, or small add-ons when you already have solid internal leadership.

2. In-house team

Pros:

• Deep product knowledge over time
• Full-time focus on your roadmap
• Strong cultural alignment if done well

Cons:

• High fixed monthly burn (salaries + taxes + benefits)
• Slow to hire the full mix of skills you actually need
• Risky early on if you don’t yet know exactly what to build

Best for: post-PMF (Product-Market Fit) stage, when you have repeatable revenue and a clear long-term roadmap.

3. Generic agency

Pros:

• Can staff a full team quickly
• Experience across industries and stacks
• Look good on paper and in pitch decks

Cons:

• Not always fluent in SaaS business models (churn, LTV, activation, etc.)
• More focused on “shipping the project” than owning the product long term
• High risk of an MVP that looks great but is hard/expensive to maintain

Best for: one-off projects or marketing/branding sites, less ideal as your SaaS product partner.

4. SaaS-focused custom software development company

Pros:

• Understand SaaS metrics and typical product journeys
• Used to thinking beyond MVP (maintenance, hosting, support, growth)
• Can bring a cross-functional team (product, UX, web, mobile, infra, QA)
• Often have proven patterns for engagement (MVP → maintenance → growth team)

Cons:

• More expensive than freelancers on paper
• You need to invest time in alignment and communication
• Not all “custom dev companies” are equally product-minded

Best for: non-technical founders or lean teams who want a long-term product partner without building a full in-house team yet.

What to look for in a long-term partner

Regardless of who you pick, some signals matter more than their logo wall:

1. SaaS literacy
   • Can they talk about activation, churn, retention, expansion, not just “screens and features”?
   • Do their case studies mention business outcomes (MRR, conversion improvements) or just tech buzzwords?
2. Beyond-MVP thinking
   • Do they bring up maintenance, hosting, support, and evolution unprompted?
   • Are they advising you on what not to build now?
3. Architecture & quality mindset
   • Do they have opinions about tech debt, testing, infra, and monitoring?
   • Can they explain trade-offs in simple language (e.g. “This is cheaper now, more expensive later”)?
4. Transparent pricing & communication
   • Can they show you how they arrived at a quote?
   • Do they offer different collaboration models and explain when each is a good fit?
5. Process for discovery and change
   • Do they push you into a fixed scope too early, or is there a clear discovery step?
   • How do they handle new information mid-project?

You’re looking for a team that behaves like a thinking partner, not a feature factory.

Engagement models and how they affect your costs

How you work with a partner often matters more than their hourly rate.

1. Fixed-price MVP, then “we’ll see”

How it works:

• Scope a fixed MVP, get a fixed price and timeline.
• After handoff, you renegotiate for anything else.

Pros:

• Clear up-front cost for the first version.
• Easier to get sign-off from investors/stakeholders.

Cons:

• Incentivises everyone to cut corners to “hit scope”.
• Post-MVP costs are completely unknown.
• Can lead to a big gap between “MVP shipped” and “who’s actually maintaining this?”

Use if: you truly only need a proof-of-concept that you’re willing to throw away.

2. Time & materials (T&M) with no clear phases

How it works:

• You pay for the time spent, month by month.
• Scope can flex freely.

Pros:

• Very flexible when you’re still learning what to build.
• You can change direction without painful change requests.

Cons:

• Harder to predict monthly/total spend.
• Easy to drift without clear goals (“busy, but what did we achieve?”).

Use if: you have a strong internal product/tech leader who can own scope and keep priorities tight.

3. Structured journey: MVP → maintenance → growth team

How it works:

1. Discovery / strategy – clarify goals, scope, and constraints.
2. MVP build – with architecture chosen for the next 1–3 years in mind.
3. Post-launch maintenance – a stable baseline for bug fixes, updates, and infra.
4. Dedicated growth team – a cross-functional squad on a predictable monthly budget.

Pros:

• Cost stays more predictable across stages.
• You don’t lose momentum after MVP.
• Maintenance and infra are treated as planned line items, not surprises.
• The same partner owns context over time (less re-explaining).

Cons:

• Requires commitment and trust on both sides.
• Needs a partner who can actually cover all stages, not just build-and-run.

Use if: you’re serious about taking a SaaS from idea to growth with a lean core team and an external product partner.

This is generally the pattern that works best for non-technical founders: phased but continuous, not “MVP, then cliff”.

Red flags that your budget will get wrecked later

Watch out for partners who:

• Never mention maintenance, hosting, or tech debt in early talks

  They either haven’t thought about it or plan to upsell you later.

• Promise complex features at suspiciously low cost

  Someone will pay that difference: you, later, in rewrites and bugs.

• Can’t explain trade-offs in plain language

  If you don’t understand the “why”, you can’t make informed decisions.

• Say yes to everything immediately

  Good partners push back and help you prioritise.

• Disappear after handoff

  If there’s no clear plan for post-launch, assume you’re on your own.

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How to talk about money with a potential partner

Some useful questions that keep everyone honest:

• “What does this look like in total over 12–24 months, not just MVP?”
• “How do you usually structure post-MVP maintenance and support?”
• “If this goes well, what would a dedicated team cost on a monthly basis?”
• “Where would you cut scope first if we needed to reduce cost?”
• “What are the typical hidden costs founders underestimate?”

A good custom software development company will have thoughtful, concrete answers – because they’ve seen the movie before.

Where VeryCreatives-type partners fit in

A SaaS-focused partner like VeryCreatives generally aims to:

• Work especially well with non-technical founders
• Map out a multi-stage journey (discovery → MVP → maintenance → growth)
• Offer clear engagement models instead of ad-hoc “hour packs”
• Help you understand and plan the full cost curve, not just the launch price

The exact labels might differ (e.g. “Essential Maintenance”, “Dedicated Growth Team”), but the principle is the same: turn your product work into a predictable, strategically managed investment, not a series of emergencies.

You’re not buying code, you’re buying a relationship

If you treat a custom software development company like a one-off vendor, you’ll get:

• Short-term optimisation on scope and price
• Long-term pain when things break or need to evolve

If you treat them like a strategic partner, you can:

• Share the real 1–3 year plan and constraints
• Co-design an engagement model that fits your stage and runway
• Make better trade-offs upfront (what to build now vs later)

In other words: the right partner + the right model doesn’t just keep your SaaS development costs under control – it makes those costs work for you, compounding into a product that actually has a shot at winning.

How VeryCreatives structures post-MVP collaborations

Let’s put all of this into something practical: what does working with a SaaS-focused partner actually look like after your MVP ships?

Below is a realistic picture of how a team like VeryCreatives tends to work with non-technical founders from “MVP is out” to “we have a real, growing product”.

The typical founder profile they’re built around

VeryCreatives is basically optimised for one type of client:

• Non-technical founders or product owners
• Building SaaS or SaaS-like platforms (B2B/B2C, marketplaces, AI-powered tools)
• Who want one partner to help with:
  • Product thinking
  • UX/UI
  • Web (and sometimes mobile) development
  • Infrastructure & maintenance
  • Ongoing iteration and experimentation

You don’t want to be the de facto CTO, PM, QA, and DevOps. You want a team that covers those bases and speaks to you in normal human language.

Big picture: a phased but continuous journey

In practice, the relationship isn’t “MVP, bye”. It usually looks more like this:

1. Discovery & roadmap (can be pre- or post-MVP)
2. MVP or major version build
3. Essential Maintenance (baseline stability and care)
4. Dedicated Growth Team (continuous iteration and expansion)

You might enter at different points (e.g. already have an MVP, but it’s messy), but the shape stays similar.

Phase 1 – Discovery & roadmap: aligning on the next 12–24 months

Whether your MVP is still on a whiteboard or already in production, there’s usually a short strategy phase where you and the team:

• Clarify business goals (revenue targets, fundraising plans, runway).
• Identify risks and constraints (technical debt, regulatory needs, budget ceilings).
• Map out a 1–3 year product arc at a high level.
• Decide what the next 3–6 months should focus on (stabilisation, PMF search, or growth).

Output is typically:

• A prioritised roadmap (features, refactors, infra work, internal tools).
• A proposed engagement model and budget, broken down into:
  • MVP / major release (if needed)
  • Maintenance baseline
  • Ongoing iteration capacity

The goal here is simple: you both see the same movie in your heads before anyone touches code.

Phase 2 – MVP or major release: build with the next stages in mind

If you’re pre-MVP, this phase is straightforward: build the first version.

If you already have an MVP (especially a “vibe-coded” one), this might be:

• A cleanup & hardening pass
• Plus a “Version 1.0” release that’s genuinely ready for paying customers

Either way, the approach is:

• Prefer solid, maintainable architecture over micro-optimising for short-term cost.
• Avoid tech choices that look cheap now but explode costs later (unnecessary complexity, fragile infra, zero tests).
• Bake in at least basic monitoring, logging, and security from the start.

You’re not aiming for perfection – just “we can live with this happily for the next 1–3 years”.

Phase 3 – Essential Maintenance: the baseline layer

Once you’re live, you don’t want to be emailing random devs every time something breaks. That’s where a structured Essential Maintenance-type layer comes in.

In practical terms, this typically covers:

• Bug fixes & incident response

  Clear rules about what counts as urgent and how it’s handled.

• Security & dependency updates

  Keeping frameworks, libraries, and packages up to date.

• Basic performance & infrastructure care

  Simple optimisations, routine checks, “turn it off if we don’t need it” cleaning.

• Monitoring & observability basics

  Error tracking, logging, alerts – so problems are spotted early.

You can think of this as your “keep the lights on and the house safe” budget. It turns unpredictable “panic payments” into a stable, monthly line item.

Ballpark-wise, for many early-stage SaaS products, this layer might sit at something like:

• A few days of engineering per month
• Enough capacity to handle typical bugs, updates, and minor tweaks

The exact number will depend heavily on complexity, usage, and your risk tolerance, but the pattern is the same: predictable protective layer.

Phase 4 – Dedicated Growth Team: the engine of progress

On top of maintenance, you usually want a steady stream of improvements: new features, UX refinements, onboarding experiments, performance boosts.

This is where a Dedicated Growth Team-style engagement makes sense. Typically, that looks like some blend of:

• 1–2 backend/frontend engineers
• 1 UX/UI designer
• 1 QA (part-time or full-time)
• A product owner / PM (either from VeryCreatives, your side, or shared)

What they do every month:

• Quarterly goals aligned with your business metrics
  • “Improve trial-to-paid conversion by X%”
  • “Reduce time-to-value in onboarding”
  • “Ship feature set Y for key customer segment Z”
• Continuous roadmap work
  • New features and improvements
  • UX and onboarding enhancements
  • Selected refactors and infra improvements tied to future work
• Structured delivery
  • Sprints or continuous delivery with clear demos
  • Regular check-ins and priority reviews

You’re no longer buying “10 developer days”. You’re buying a product engine with a predictable monthly cost.

Putting it together: an example 6–12 month collaboration

To make this concrete, imagine you arrive with a rough MVP:

Month 0–1 – Audit & plan

• Codebase and infra audit
• Product and UX review
• Risk assessment and debt hotspots
• 6–12 month roadmap + costed engagement proposal

Month 2–3 – Stabilise & harden

• Fix the scariest bugs and architectural problems
• Add monitoring, better logging, and safer deployments
• Clean up core flows (signup, onboarding, main value path)

Month 4–6 – Iterate & learn

• Essential Maintenance in place (small, steady baseline)
• Growth Team focuses on:
  • Improving activation
  • Shipping 1–2 key features
  • Reducing manual support work with simple internal tools

Month 7–12 – Scale what works

• Iterative cycles based on data and user feedback
• Deeper features, better onboarding, internal tooling expansion
• Periodic infra reviews and optimisations as usage grows

At each stage, you know:

• What you’re paying per month
• What outcomes you’re aiming for
• Who’s doing what (you vs partner)

How this keeps your costs sane (instead of surprising)

This kind of structure helps avoid the classic budget traps:

• Trap: “Cheap” MVP that needs a rewrite 12 months later

  Instead: MVP + cleanup are scoped with a 1–3 year horizon in mind.

• Trap: Post-launch chaos with random invoices

  Instead: Essential Maintenance sits as a steady baseline, with clear scope.

• Trap: Big gaps between releases, low momentum

  Instead: Growth Team has a clear capacity and goals every month.

• Trap: No idea what the total cost will be over 18–24 months

  Instead: You have a roadmap with budget envelopes per phase, not just a single MVP quote.

For non-technical founders, this is often the difference between feeling like you’re in control of your SaaS development costs vs constantly being surprised by them.

How to make the most of a setup like this

If you work with a team like VeryCreatives, you’ll get the most value if you:

• Share your real constraints (runway, fundraising plans, personal risk appetite).
• Be clear about your business priorities, not just your feature wishlist.
• Embrace the idea of continuous iteration, rather than “one giant launch”.
• Treat the partner as a strategic collaborator, not just a pair of hands.

They bring the technical, UX, and process expertise; you bring the market and vision. The engagement model exists to make that collaboration sustainable – financially and operationally – beyond your MVP.

From here, the last step in the article is to pull everything together: the key takeaways and a simple checklist you can use to sanity-check your own SaaS budget plans.

Final thoughts: Don’t just launch a SaaS — build one you can afford to grow

If there’s one idea to walk away with, it’s this: your MVP is just the downpayment. The real cost of SaaS lives in everything that happens after launch – maintenance, infrastructure, iteration, support, and the endless little decisions that decide whether your product gets better or quietly decays.

Across the whole journey, a few patterns repeat:

• Treat your product as a 1–3 year commitment, not a one-off project.

• Budget intentionally for the four big buckets: keeping it alive (maintenance), running it (infra), making it better (iteration), and supporting the people who use it (support + tooling).

• Choose partners and platforms with future you in mind—cheap shortcuts now often show up later as tech debt, rewrites, and unpredictable bills.

Your next step doesn’t need to be huge. Do this:

1. Sketch your rough 12–24 month product budget (even as ranges).
2. Divide it across those four buckets, based on your stage.
3. Pressure-test it with someone who understands SaaS (an internal lead or a partner like VeryCreatives), and adjust until it feels both realistic and survivable.

If you do that, you’re no longer just asking “How much will it cost to build this?”

You’re answering a far better question: “Can we afford to keep making this product better?” And that’s where real SaaS businesses are built.