AI Systems
- production AI systems shipped
- 32
- median answer accuracy at launch
- 94%
- average inference cost reduction
- 71%
Deliverables
Concrete artefacts, handed over in your repositories.
Evaluation harness
A versioned test set with graded rubrics, run on every prompt or model change. You get a number that moves, not a vibe.
Retrieval layer
Chunking, embedding, hybrid search and reranking tuned against your corpus, with the recall measurements to prove the tuning worked.
Serving path
Streaming responses, caching, fallback models, rate limiting and a circuit breaker for when a provider has a bad afternoon.
Observability
Every call traced with its prompt, retrieved context, latency and cost, so a bad answer can be reconstructed instead of guessed at.
What this covers
- Retrieval-augmented generation over your own corpus
- Agent and tool-use workflows with hard guardrails
- Offline and online evaluation harnesses
- Fine-tuning, distillation and model routing
- Token accounting, caching and cost control
- Human-in-the-loop review and escalation paths
What we usually reach for
- Claude
- OpenAI
- pgvector
- LangGraph
- Modal
- Braintrust
- Temporal
Tooling is a consequence of the problem, not a starting position. If your team already runs something that works, we use that rather than charging you for a migration you did not ask for.
AI Systems, specifically
Almost never at the start. Frontier models plus good retrieval beat a fine-tune for the first several months, and the evaluation set you build in the meantime is exactly what you would need to fine-tune well later.
You constrain what it can say and measure when it strays. Grounded generation with citation checks, refusal paths when retrieval confidence is low, and an eval suite that scores unsupported claims as failures.
You do. Code, prompts, eval sets and infrastructure definitions live in your repositories from the first commit.
Other services
Tell us what you are building.
A system you want built, a model that has to survive real traffic, or a process that should have been automated a year ago. The first conversation costs nothing, and occasionally ends with us telling you not to build it.
Reply within one working day
A person, not an autoresponder.
A 30-minute call, no deck
We ask about constraints, not budget.
A written view within a week
Including the case for not proceeding.