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SaaS Development Agency
The SaaS development agency that tests your riskiest assumption first
Most failed SaaS projects fail on the product bet, not the code. We build AI-native SaaS from MVP to production, but we start by shipping the one feature that proves or kills your core assumption. Next.js, Supabase, and Claude, with the strategy, build, and maintenance in one team.
- MVP to production, one team
- AI-native by default
- Next.js, Supabase, Claude, Vercel
Trusted by teams at
What a SaaS development agency should actually do
A SaaS development agency turns a product idea into running software: architecture, database design, auth, billing, the interface, and the deployment pipeline. Done well, it also protects you from the classic failure mode, which is spending months polishing features nobody has validated. We sequence every build around the riskiest assumption: the one claim that, if wrong, makes the rest of the roadmap irrelevant.
AI-native changes what SaaS means. The products winning now do not bolt a chatbot onto a CRUD app; they build retrieval, agents, and generation into the core workflow. That takes engineering most agencies have not done in production: eval sets before launch, fallbacks when the model is wrong, and cost controls so your margin survives your own success.
We build on a boring, proven stack: Next.js on Vercel, Supabase for the database and auth, Claude for the AI layer, PostHog for analytics. This site runs on the same stack. Boring infrastructure is a feature: it means your budget goes into the product bet, not into fighting exotic tooling.
Where this wins
Founders with a validated problem and no product yet
You know the pain and the buyer. We ship an MVP built around your riskiest assumption so real users answer the question before the budget runs out.
Companies adding AI features to an existing product
RAG over your data, agent workflows, or generation inside the product. We build the AI layer with evals and guardrails, not a demo that falls over on real input.
Teams whose MVP is buckling under real usage
The prototype won customers and now it drops requests. We harden the architecture, add monitoring, and pay down the debt in order of what breaks next.
When NOT to use this
- · You have not talked to a single potential customer yet. Cheaper to run ten conversations than to build the wrong MVP; do that first.
- · You want a fixed-scope build of a 40-page spec with no room to learn. We work in validation loops, and forcing waterfall through us wastes what you are paying for.
- · You need a native mobile app as the core product. Our production depth is web SaaS on Next.js; a mobile-first shop will serve you better and we will say so.
How we take SaaS from idea to production
The process mirrors our ai-product-build workflow: name the riskiest assumption, ship the thinnest thing that tests it, then invest in what the evidence supports. Production quality from the first deploy, because MVPs have a habit of becoming the product.
01
Assumption mapping
We pressure-test the product thesis and write down the riskiest assumption: the claim that kills the product if false. Scope gets cut to whatever tests it fastest.
DeliverableProduct brief with a ranked assumption list
02
Architecture and skeleton
Next.js app, Supabase schema, auth, and deploy pipeline on Vercel. Days of setup, not weeks, because the stack is deliberately standard.
DeliverableDeployed skeleton with auth and CI
03
Core loop build
The one workflow users must love gets built end to end, including the AI layer with an eval set and fallback paths where it applies.
DeliverableWorking core product loop in production
04
Real-user validation
Instrumented with PostHog, in front of real users. We read the funnels and session data with you and decide from evidence, not opinions.
DeliverableUsage data and a prioritized iteration plan
05
Harden and extend
What survived validation gets production depth: monitoring, rate limits, billing edge cases, and the next features in evidence order.
DeliverableProduction SaaS with a maintenance plan
Typical timeline
Working MVP typically 4-6 weeks; production hardening and iteration continue from there
Stack we build with
Next.js · Vercel · Supabase · Claude (API) · PostHog · TypeScript
SaaS products we build
AI-native vertical SaaS
Industry tools where retrieval and generation sit inside the core workflow, not in a bolt-on chat tab.
Internal tools promoted to products
The spreadsheet-and-scripts system your team built becomes real multi-tenant software you can sell.
RAG-powered knowledge products
Search and answers over proprietary documents, with citations, access control, and an eval set that keeps quality measurable.
Agent-driven workflow products
SaaS where an agent executes multi-step work for the user, with human review queues where the stakes require them.
Customer portals and dashboards
The self-serve layer on top of your existing service business: accounts, data, documents, and billing in one place.
MVP rescues
A prototype from another team gets audited, stabilized, and rebuilt where necessary, keeping what actually works.
Book a Free Product Call
Find out what to build first, and what to skip
A 30-minute call: we identify your riskiest assumption, sketch the thinnest MVP that tests it, and tell you honestly whether you should be building yet at all.
Book a 30min Free Strategy Call
In this call, we'll walk through your project scope, timeline, and goals - so we can both check if we're a fit. No obligation, no slide deck, just a working session.
Don't want a call? Email walid@ayautomate.com
Opportunity Map
Implementation Path
Fast Follow-Up
“The team is super fast - sometimes we had to slow them down. We managed to scale the company without investing into hiring.”
Elie Salame
COO, Adstronaut.io
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Phone Call
In-Person
We've created products featured in
Walid Boulanouar
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If you're serious about optimizing your operations or scaling smarter, book your spot now. Otherwise please don't waste your time and our time.
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FAQ
SaaS Development Agency Questions
What does it cost to build a SaaS with an agency?+
A focused MVP is typically a five-figure engagement over four to six weeks; production hardening and iteration continue from there. We scope after the product call because the honest driver is scope, not hours: the fastest way to lower the price is to cut the MVP to the features that actually test your assumption, and that cut is the first thing we do together.
Why not use a cheaper offshore dev shop or a no-code builder?+
If your product is a standard CRUD app and you mainly need hands on keyboards, a cheaper shop can work. Where we earn the difference is judgment: cutting scope to the real bet, and building AI features that survive production, with evals, fallbacks, and cost controls. Code is cheap to write and expensive to write twice.
Do you only build AI products?+
No, but we default to asking where AI belongs in the product, because that is where new SaaS wins or loses right now. If your product does not need AI, we will not force it in; unnecessary AI adds cost and variance for nothing.
Who owns the code and infrastructure?+
You do, from day one. The repo, the Vercel project, the Supabase instance, and every API key live in your accounts. If we part ways, you lose nothing but us.
What happens after the MVP ships?+
We read the usage data with you and decide the next move from evidence. Some clients take a clean handover with documentation; most keep us on for iteration and maintenance, because the weeks after launch are where the product direction actually gets decided.