Services/03
AI that survives contact with production.
The gap between an impressive AI demo and a dependable AI system is data engineering. We build LLM-powered agents, document pipelines, and natural-language interfaces with evaluation harnesses, guardrails, and cost controls — and we fix the data layer underneath when that's the real problem.
Signals
You probably need this if…
- 01An AI pilot impressed everyone and then quietly never shipped
- 02Your LLM bill is growing faster than the value it produces
- 03You want AI features but your data is too scattered or dirty to feed them
- 04Teams are pasting sensitive data into public chatbots because there's no sanctioned tool
- 05Leadership wants an 'AI strategy' and you need something real to show
What we build
Deliverables, not decks.
LLM agents & workflows
Tool-using agents wired into your systems — Claude, OpenAI, Gemini, Bedrock, or self-hosted models — with structured outputs, evaluation suites, and human-in-the-loop checkpoints where the stakes demand them.
Document intelligence
Extraction, classification, and summarization pipelines for contracts, claims, and forms — with confidence scoring and review queues, not blind automation.
Natural-language analytics
Ask-your-data interfaces grounded in a governed semantic layer, so the answers are right and traceable — not plausible hallucinations.
AI cost & latency optimization
Model routing, prompt caching, batching, and fine-tuning evaluations that routinely cut LLM spend 40–70% without losing quality.
→ Start a project
Have a ai systems problem on the roadmap?
Describe it in three sentences. We'll come back with how we'd approach it, what it likely costs, and whether we're the right team — usually within two business days.