ai systems
models that earn their place in production
A model in a demo and a model in production are different problems. We build the parts around the model that decide whether anyone can rely on it: retrieval grounded in your own data, guardrails that make it refuse rather than guess, and evaluation that catches a regression before your users do. The goal is a system your team can trust and change without holding its breath.
signs you need this
- an off-the-shelf chatbot answers confidently and wrongly, so people stopped using it
- you want to ship an AI feature but cannot tell whether it is getting better or worse
- answers are not tied to a source, so nobody can check them
- costs or latency are creeping and no one owns the budget
what we do
- retrieval and context pipelines over your own data
- agent and tool-use workflows with clear failure modes
- evaluation harnesses so a prompt change cannot regress silently
- cost and latency budgets tracked per request
related work
ai systems in practice.
how we engage
ways to work together.
scoped project
a defined problem with a clear finish line
We agree the outcome, break it into observable milestones, and build to them. Best when you know roughly what you need and want a fixed shape around it.
- a written scope and milestone plan
- regular working demos, not status decks
- handover with tests, dashboards, and a runbook
embedded engineering
a team that needs senior hands for a stretch
We work inside your team and process for a set period - reviewing, building, and levelling up the codebase alongside your engineers.
- work in your repos, standups, and review flow
- focus on one or two hard problems at a time
- knowledge left behind, not hoarded
advisory & review
a decision or a system you want a second read on
A shorter engagement to look hard at what you run and tell you the truth about it - an architecture review, an AI feasibility read, a performance audit.
- a focused review of code, data, or architecture
- a written findings doc with priorities
- a call to walk through it and answer questions
more of what we do
the other two disciplines.
start here
have a system that used to feel fast?
Tell us what it does and where it hurts. We’ll tell you honestly whether it needs sharpening or rebuilding - and what that would take.