AI integration
AI features that are useful, reliable and part of your product
We add large language models to your product and workflows where they help: assistants, search over your own content and automations, with evaluation built in.
Who it's for
- Your team wants to use AI but doesn't know where it would actually help.
- A prototype chatbot works in the demo but gives wrong answers to real users.
- People spend hours on repetitive work like triage, data entry or summarising.
- Your users can't find answers buried in your docs, tickets or knowledge base.
What we do
Assistants and chat
In-product assistants that answer from your data and act through your APIs.
Search and RAG
Retrieval over documents, tickets and databases, with sources cited in every answer.
Workflow automation
Classification, extraction and summarisation wired into the tools your team already uses.
Evaluation
Test sets and automated checks that measure answer quality before and after every change.
Guardrails and privacy
Access control, redaction and limits, so models only see and do what they should.
Cost and latency
Model choice, caching and streaming tuned to keep responses fast and affordable.
How the work runs
Explore
We look at your workflows and data and pick the use cases with the clearest return.
You get: A short list of use cases with their expected value and risk.
Typically 1 week
Prototype
We build a working prototype on real data and measure it against a test set.
You get: A prototype and an evaluation report.
Typically 2–3 weeks
Build
We integrate the feature into your product with guardrails, logging and fallbacks.
You get: A production feature behind a flag.
Typically 3–8 weeks
Improve
We monitor real usage, grow the test set and tune prompts, retrieval and models.
You get: Quality you can measure over time.
Ongoing, as needed
Deliverables and stack
What you receive
- Use-case assessment
- Working prototype
- Evaluation test set and report
- Production integration
- Usage and cost monitoring
- Documentation
Tools we use
- Anthropic Claude
- OpenAI
- Vercel AI SDK
- PostgreSQL
- pgvector
- TypeScript
- Python
How we work together
A defined project
We scope it and send you a fixed quote.
Hourly, USD 50/h
Our team works through your backlog, week by week.
Questions
Which AI models do you use?
We work with models from Anthropic, OpenAI and others, and choose per use case on quality, speed, cost and where your data may be processed. The integration is built so the model can be swapped.
Is our data safe?
We use API terms that exclude your data from model training, send models only the data each task needs and keep access control in your own systems.
How do you stop the AI from making things up?
We ground answers in your own content, show their sources and measure accuracy against a test set before launch. Where a wrong answer is costly, a person reviews it first.
We're not sure where AI fits. Can you still help?
Yes, that's what the first phase is for: we look at your workflows and tell you where AI is worth it, and where it isn't.
How is a project priced?
We quote a fixed price for a defined project once we understand the scope, or work hourly at USD 50/h. Tell us about your project and we'll reply with a proposal within 48 hours.