Agentic systems, MCP servers, and fine-tuned clinical models built against real EHR data. Tool use, evals, guardrails, and the observability work that keeps an agent running long after the demo is over.
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The AI work we take on falls into three patterns. Each one is scoped to a workflow, not a checkbox. Each one ships with the scaffolding that keeps it operable once we hand it back, and every engagement is delivered by our forward deployed engineers, embedded in your repo.
Multi-agent workflows that reason, plan, and execute against real clinical data. Tool use, evals, and the boring observability work that keeps them running past day 30. We've shipped these against live EHR data, not toy demos.
Custom MCP servers wired into the clinical systems your agents need to read. Tool definitions, scoped resources, and policy gates so an agent can place the order, post the note, and stay inside the BAA at the same time.
When a general-purpose model is the wrong tool. Domain-specific training on medical datasets for the narrow cases where you need a smaller, faster, owned model with predictable behavior.
Three shapes of work we see repeating. Each one earns its place by moving a metric the operator already runs against, not by sounding good in a slide.
Radiology workflow that surfaces likely findings on study load, with the precision and recall numbers attached.
Treatment recommendations grounded in patient history and current evidence, in the chart, not a separate UI.
Compound search and trial design tooling that compresses the early-phase loop without breaking governance.
A short read first, then a focused build. We do not start by staffing a team. We start by writing down what is worth building and what the eval surface looks like.
A written read on what to build, what to retire, and where the eval surface lives. No team commitment yet.
MCP server, agent harness, and an eval suite that gates the merge. Synthetic data first, then your data.
Live integration, audit trail, traces, and the on-call shape. Canaries before the broader rollout.
Runbooks, eval baselines, and the team to keep it healthy. We stay on retainer if you want, not because you have to.
A senior pod, embedded in your codebase, scoped to a single clinical workflow. Working system in six to twelve weeks, not a roadmap. For a concrete look at the safety architecture, read how we built a safe triage agent.