Service 02
LLM & Agent Development
Production language models and agents with evals, not a weekend chatbot.
- Evals
- Retrieval
- Tool use
An agent without evals is a demo with a deploy button.
The hard part is not making it work once. It is knowing, on Tuesday, whether the change you shipped on Monday made it better or quietly worse — and being able to show that before a customer does the checking for you.
So the measurement comes first: cases drawn from your real work, scored the way you would score them, run on every change. After that, prompts, retrieval and tool calls stop being opinions and become engineering problems with a number attached.
What we actually do
- An eval suite built from your own cases, not a public benchmark
- Retrieval over your documents, with the retrieval itself measured
- Tool and function calling wired into the systems you already run
- Guardrails on the paths where a wrong answer costs money
- A defined behaviour for when the model is slow, wrong, or down
- Cost and latency budgets enforced in code, not in a document
Who it’s for
Teams whose assistant, classifier or agent has to be trusted by someone outside the team that built it.
How it runs
Usually four to ten weeks, in two-week sprints, with something you can try at the end of each one.
Start with the problem.
Tell us what you’re working on and whether llm & agent development is really what it needs. An engineer reads every enquiry.