Custom AI apps and SaaS — fixed scope, fixed price.
Aiprocesai builds custom AI apps, SaaS tools, and internal business systems when a standard website, spreadsheet, or off-the-shelf automation tool is no longer enough. Every project starts with a written spec and a fixed quote, ships with AI features (LangChain, RAG, vision) integrated from day one, and ends with full code and IP transfer to the client.
Built on Next.js, Supabase, and LangChain. Internal dashboards, iOS/Android apps, and legacy-system modernisation — with full IP transfer on delivery.
A documented spec before code starts. No surprise hourly bills.
The codebase and intellectual property belong to you on day one of production.
LangChain and vector search are part of the architecture from the start, not added at the end.
Capabilities
What we build
Operational dashboards your staff can query in plain language (e.g. "show me SKU returns in Q3"). Pulls from your existing database; surfaces insights without manual SQL.
iOS / Android apps for field operations: logistics check-in, on-site inspection, photo-based defect logging. One codebase, both platforms.
Customer-facing SaaS with subscription billing (Stripe), multi-tenant authentication, and an admin back-office. We deliver MVP first, then iterate.
Wrap an old ERP or in-house system with a modern web UI so your team can work in a browser instead of a green-screen terminal.
Process
From spec to launch in three phases
We map the workflow, document the data model, and define acceptance criteria. Output: a written spec and a fixed quote.
We build against the spec with regular checkpoints. AI features are integrated from day one, not bolted on at the end.
Production deployment, team training, and full codebase + IP transfer. The post-launch support window is defined and agreed before launch.
Delivery model
Fixed-scope vs Time & Material — honest tradeoffs
We default to fixed-scope projects because most clients want to know the cost before they commit. Here is when each model actually makes sense.
- Useful when the scope is genuinely unknown — research, exploratory R&D, or a long-term partnership.
- The longer the work runs, the higher the bill. Budget is open-ended.
- Requires close client involvement to keep direction.
- Fixed price against a documented spec. You know the cost before code starts.
- Scope changes are quoted separately so the original timeline stays intact.
- AI features are part of the spec, not bolted on at the end.
Stack
Technologies we use
Case studies
Related: how we ship real automation projects
Most of our application work starts with the same audit step as our automation pilots. Two recent automation cases that show our delivery approach:
Related
Related services and pricing
Honest fit
When this is not the right fit
Questions
Frequently asked questions
- When does custom development make more sense than a SaaS tool?
- A SaaS subscription is faster and cheaper for standard use cases. Custom development becomes the right choice when the process is specific to your business (custom logic, custom data, custom integrations) and a SaaS tool would force you to bend the process to fit the product. We tell you honestly when an off-the-shelf SaaS would be the better answer.
- How do you keep fixed quotes and delivery timelines?
- Before any coding starts we run a spec-driven phase: we document the functionality, the data model, and the acceptance criteria, then quote a fixed price against that spec. Scope changes are quoted separately so the original timeline stays intact.
- How long does a typical project take to deliver?
- Timeline depends on scope. We confirm a realistic delivery window during the spec phase, before any code is written, so the schedule reflects the actual data, integrations, and AI features the project needs.
- What is your tech stack?
- Web front-end and back-end: Next.js (React) and Node.js / TypeScript. Mobile: React Native. Data: Supabase / PostgreSQL. AI: LangChain and LangGraph (Python or TypeScript) talking to Azure OpenAI or Anthropic Claude.
- Do you build computer-vision features?
- Yes. We use GPT-4o vision and specialised open-source models for object detection, document understanding, and visual defect detection in production environments.
- Do you handle hosting and maintenance after launch?
- We deploy on Vercel, Supabase, Azure, or your own infrastructure — whichever fits your data residency and ops setup. The post-launch support window is defined and agreed before launch — it can be a fixed handover period, an ongoing retainer, or per-change quoting, depending on what fits the project.
- Who owns the intellectual property?
- You do. 100% of the codebase and IP is transferred to the client at the end of the project. You can hire any team to maintain or extend it later — no lock-in.
Tell us about the project
Describe what you want to build. We come back with a scoping plan and a fixed quote within 48 hours.
- ✅Free 30-min audit
- ⚡Response within 24 hours
- 📋Firm pricing quote
- 🔒GDPR compliant
- 🤝Zero initial obligations