Who owns the code and the models?

You do, from the first commit. Everything lands in your repository and your cloud tenancy. Any prompts, evaluation sets and fine-tunes are yours too.

Do we need our data ready before you start?

No. Data being messier than expected is the normal case, not the exception, and finding that out is part of the first two weeks rather than a reason to delay them.

What if the AI part turns out not to work?

Then we say so, early, and you have spent two weeks rather than two quarters. A benchmark that comes back short is a useful result: it is a lot cheaper than a launch that quietly disappoints.

All services

Full-Stack & AI Development

Web apps, APIs, LLM features and agents are no longer separate projects with separate teams; a product needs all of them and they have to agree with each other. One team builds the whole thing, in your repo and your cadence, with no account-management layer in between.

Scope this with us

Built with

TypeScript
Next.js
Node.js
Claude
LangGraph
Postgres

Shape
We cut the scope down to what the first release genuinely needs, and write down what we are deliberately leaving out. Anything model-backed gets its accuracy bar agreed here, not after it is built.
Build
An experienced team works in your repo, on your branch, at your cadence. AI carries the repetitive code and the tests; the architecture and every real decision stay with a person.
Prove
Every AI-backed path gets an evaluation harness you can run in CI, so quality is a number you own rather than an impression from a demo.
Ship, then keep shipping
Day fourteen it is running in your environment, with the pipeline, the tests and the decision records. Then a release every fortnight for as long as you need us.

What Full-Stack & AI Development covers

Product build, from empty repo to production

Greenfield work where the whole thing is ours to get right: schema, API, interface, deployment and the release process that keeps it moving. One team owns all of it, which is why the interface never waits three weeks on an endpoint that was never specified.

What that means

Architecture agreed before the first commit
Deployed to your cloud from week one
A release cadence you can plan around

LLM features grounded in your own data

Retrieval over your content, with citations, a confidence floor and an evaluation harness. The interesting question is never which model to use; it is whether the answers are good enough to put in front of a customer, and that is measurable before you commit to it.

What that means

Answer-quality benchmark you can re-run
Citations back to source documents
A defined behaviour for "I do not know"

Agents with contracts, not vibes

Every tool an agent can call has a typed contract, a retry policy and a human checkpoint where the action is expensive or irreversible. An agent that can spend money or email a customer gets a gate; an agent that reads gets latitude.

What that means

Typed tool contracts with validation
Retries, timeouts and idempotency
Human approval on irreversible steps

The delivery machinery, built in from day one

Tests, CI, migrations and observability are part of the first fortnight rather than a hardening phase that never gets scheduled. This is the part that decides whether release forty is as calm as release one.

What that means

CI running on the first pull request
Migrations that roll forward and back
Traces and alerts on the paths that matter

Have a product that needs building end to end?

Scope this with us

Retrieval over your own content
Answers grounded in your documents with citations back to the source, so a reader can check the machine rather than trust it. The permissions of the underlying content are carried through to the answer.
Agents that can act, within limits
Tools an agent may call are typed, validated and rate limited, with a human checkpoint anywhere the action costs money or cannot be undone.
Measured before it ships
An answer-quality benchmark you can re-run after any prompt, model or data change. Without one, every future change is a guess about whether things got better.

Why teams pick us for Full-Stack & AI Development

One team across the whole stack

Web, backend, model and infrastructure sit with the same people, so nothing is lost in a handover between vendors who each think the other owns it.

You own it from the first commit

The code is in your repository, on your cloud account, under your licence. There is no runtime of ours you have to keep paying for to keep the thing running.

The risky part goes first

The unknown that could sink the budget gets built in week one, not deferred to a phase four that arrives with no money left to fix it.

Working software every two weeks

Not a status deck. Something deployed you can open, use and argue with, which is the only progress report that cannot be fudged.

What you receive

Working software every two weeks
Answer-quality benchmark for anything AI-backed
Test suite and CI pipeline you own
Architecture decision records for every major call

The stack we build this on

Languages and frameworks

TypeScript
React
Next.js
Node.js
Python
Go

AI and models

Claude
OpenAI
LangGraph
LlamaIndex
pgvector
Evaluation harnesses

Data and storage

PostgreSQL
Redis
S3
Prisma
Drizzle

Cloud and delivery

AWS
Vercel
Docker
GitHub Actions
Terraform

Quality and observability

Playwright
Vitest
OpenTelemetry
Sentry
Grafana

Often paired with

AI Strategy & ConsultingWhere AI is worth applying, and where it is not.View practice Product & UX DesignInterface and flow design, built to be built.View practice Mobile App DevelopmentiOS, Android, and cross-platform apps, including on-device AI.View practice

Yes, and most of the time that is what happens. We read what is there, agree the conventions with your team, and work inside them. We will tell you if something needs replacing, but we will not rewrite it because it is not how we would have done it.

Full-Stack & AI Development