AI integration
AI features that hold up on real data: assistants, triage, search over your documents, and agents with a human in the loop.
- Typical timeline 2 to 6 weeks
- Fixed price per milestone
What we build
Getting a model to answer once is easy. Getting it to answer correctly every day, at a cost you can predict, is the job. We start from your real data, build an evaluation set before we build the feature, and measure the model against it. Anything that sends money, mail, or changes a record waits for a person to approve it. You get a dashboard that shows what the AI did, what it cost, and where it was unsure.
- 01Customer support assistants
- 02Email and document triage
- 03Search and Q&A over your documents
- 04Data extraction from PDFs and forms
- 05Agents that act inside your tools, with approval gates
- 06AI features inside an existing product
What you walk away with
- 01Working AI feature or assistant
- 02Evaluation set on your data
- 03Integration with your tools
- 04Cost and quality dashboard
- 05Runbook
- 0630-day fix warranty
Typical timeline
2 to 6 weeks
Ranges from past projects. Your proposal states your dates.
How the weeks run
- 01DiscoveryDay 1 to 2
- 02DesignDay 3 to 5
- 03DevelopWeek 1 to 3
- 04DeployWeek 4
What we build it with
- Fixed price per milestone
- Senior review on every change
- Your repo and accounts from day one
- Claude (Anthropic)
- OpenAI
- Python
- TypeScript
- Postgres with pgvector
- Microsoft Graph and Google Workspace APIs
Before you ask
What technologies do you work with?
Mostly TypeScript, React, Next.js, Node.js, Python with FastAPI, PostgreSQL, and Docker, deployed to Railway or your own cloud. React Native or Swift for mobile. Claude and OpenAI models for AI features. If you already have a stack, we usually work in it.
Does AI train on my code?
No. The agents work in your repo for your project only. They run on accounts with training on customer data turned off, and we will confirm that in writing on request.
Do you sign NDAs?
Yes, before you share anything sensitive. Your ideas and business information stay confidential.
What happens when an agent writes something wrong?
It happens on most projects. Tests catch some of it and the reviewing engineer catches the rest, and the change goes back with notes. It does not reach your users.
Often paired with
- Business automationThe manual work your team repeats every week, done by software that tells you when it breaks.Typical timeline: 1 to 4 weeks
- Data extractionCollect, clean, and deliver the data your business needs, on a schedule, without babysitting.Typical timeline: 1 to 3 weeks
- API and backend developmentAPIs, jobs, queues, and integrations, with clean contracts and documentation.Typical timeline: 3 to 6 weeks