AI Pipelines · Service 04
Production AI that actually runs your operation.
Document processing, retrieval, and agents built with cost guardrails, eval harnesses, and monitoring — AI systems that survive contact with real data.
10M+↗
Pages processed
98%↗
Retrieval accuracy
$0.08↗
Avg cost per doc
12↗
Systems in production
What we deliver
AI Pipelines, done to a production standard.
Most AI projects die in the gap between demo and production. The demo works on three hand-picked examples; the production system has to work on ten million messy ones, stay within budget, and not hallucinate its way into a liability.
We build AI systems for that reality. Retrieval that's measured, agents that are bounded, document pipelines that are observable, and an eval harness shipped on day one so you always know whether the system is actually working — and what it costs.
Document processing
Ingest, extract, and structure documents at scale with measurable accuracy.
Retrieval (RAG)
Grounded retrieval systems that cite sources and stay accurate as data grows.
AI agents
Bounded, tool-using agents that automate real tasks with guardrails.
Evals & monitoring
Eval harnesses and dashboards so you know quality and cost in real time.
What we build with
The stack behind the work.
Anthropic
Frontier models
OpenAI
Models + embeddings
pgvector
Vector search
Evals
Quality harness
Observability
Cost + tracing
TypeScript
Pipeline glue
How we work in ai pipelines
The standards we hold on every build.
Every AI system we ship includes an eval harness from day one. We don't deploy AI without a way to measure if it's working.
Cost is a first-class metric. We instrument per-request cost and set guardrails before anything reaches production.
We design for failure modes — what happens when the model is wrong, slow, or down — because in production, it will be.
We ground responses in retrieval, cite sources, constrain outputs, and measure accuracy with evals. We design the system so wrong answers are caught, not shipped.
We instrument per-request cost from day one and engineer for budget — model selection, caching, and guardrails keep cost predictable.
We're model-agnostic and route to the right model per task — frontier models where quality matters, smaller models where cost does.
Yes. We build secure pipelines around your documents and systems, with access controls and no training on your data without consent.
An eval harness ships with the system — a measurable, repeatable test suite that tells you quality is holding as data and prompts change.
No. Production AI is retrieval, evals, monitoring, cost control, and failure handling — the API call is the smallest part.
Often paired with
AI Pipelines · Ready to build?
Build the AI that actually runs your operation.
Tell us the problem. We'll build the system that solves it — and prove it works.