LLM applications
Chat, copilots and generation inside your product — not a demo beside it.
- Stream tokens straight into your UI
- Call your own functions mid-answer
- Return typed, validated output
LLM apps, agents, mobile and web — demoed on your own staging as we build.
Chat, copilots and generation inside your product — not a demo beside it.
Multi-step work that runs itself, and stops where it should.
Answers grounded in your own documents, with citations anyone can check.
iOS and Android, built and shipped to the stores — model or no model.
Dashboards your customers use daily, and sites that load fast. Built, not templated.
The wiring between systems that were never designed to talk to each other.
Something that works on ten examples is a demo. Retrieval quality, evals, cost and latency are the work.
Book a 30-minute callAgents work inside the tools your team already uses.
Grounded answers with citations anyone can check.
Multi-step automation with guardrails, retries and a human gate.
Four steps, same order every time. You always know what happens next.
Thirty technical minutes with an engineer, working out whether AI fits and which feature is worth building first.
One feature, fixed scope, fixed price. Retrieval, tools and guardrails designed before code is written.
Weekly demos on your own staging, with the eval suite running on every change.
The repo, prompts and eval suite are yours either way. Continue monthly, or take it in-house.
Agents read where work arrives, decide against your rules, and write the result back.
Triage today's support threads and open issues for the real bugs
Reproduced, and filed as a bug.
Merged into an existing issue.
Answered from three cited sources.
Refund request, outside policy.
Every engagement is judged on one thing: what your team stops doing by hand.
Repo, prompts and eval suite — yours from day one
Send the problem, not a specification. If we are not the right team, we will say so.