Custom AI Applications, From Architecture to Launch

Some problems deserve more than a workflow — they deserve a product. We design and build custom AI applications end to end: customer-facing AI features in your SaaS, internal platforms that become your company's operating system, and standalone AI products taken from idea to launch.

Full-stack means full-stack: Next.js and React frontends, Node/Python backends, Supabase/PostgreSQL data layers, and Claude/GPT intelligence — engineered as one system with evaluation and monitoring built in.

Sound familiar?

Duct-taped internal tools

The business runs on spreadsheets and scripts that were temporary three years ago.

AI product ideas stuck at idea

You can see the product; hiring an AI-capable team to build it is a year-long detour.

Agencies that hand off and vanish

Code delivered, context lost, every change a new negotiation.

What we build

Product & system architecture

Data model, AI layer, integrations and infrastructure designed before code.

Full-stack build

Frontend, backend, database and AI orchestration shipped in weekly increments.

Evaluation & guardrails

AI behavior tested, constrained and monitored like any other production system.

Deployment & handover

Cloud deployment, documentation and optional ongoing engineering partnership.

Outcomes clients measure

How we work

Every engagement follows our six-stage process — Discovery, Architecture, Implementation, Testing, Launch, Optimization — with weekly demos so you see progress, not promises. Read more about how we deliver and why teams choose Ignifer Labs.

Frequently asked questions

What does a typical build cost and take?

Focused internal tools ship in 4–8 weeks; fuller products in 2–4 months. After discovery you get a fixed-scope proposal — we don't do open-ended hourly builds.

Who owns the code and IP?

You do, entirely — repositories, infrastructure and documentation are handed over in your accounts.

Can you take over an existing half-built project?

Often, yes. We audit the codebase first and tell you honestly whether to continue, refactor or restart.

Industries we apply this in

Related services

Related work & further reading

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