Services

Four engagements.
One through-line.

Each engagement stands alone, and each one makes the next possible. You can stop after any stage — we'd rather you do that than carry a system you can't operate.

Stage 01 · 2 weeks · fixed fee

Readiness & opportunity map

We interview 8–12 people across your business, shadow the workflows they describe, and map each one against what frontier models are actually good at today. The output is a ranked opportunity list with effort, risk, and expected payback — plus a concrete pilot plan.

Outputs

  • Opportunity map (12–18 workflows, scored)
  • 3–5 pilot candidates with ROI modeling
  • Pilot plan: scope, eval set, exit criteria
  • Executive briefing deck
Good fit if
  • You've had 2+ AI "demos" that didn't go anywhere
  • Leadership wants a defensible plan, not a pitch
  • You need a pilot that survives a CFO review
  • Regulated industry, or soon-to-be

Stage 02 · 6–8 weeks

Measured pilot

One workflow, instrumented properly. We build the evaluation harness before we touch the model — accuracy against a gold set your experts validate, cost per run, reviewer time, and the exit criteria that determine whether it goes to production.

Outputs

  • Evaluation harness with versioned test set
  • Baseline (human) vs. model performance
  • Cost-per-run economics
  • Go/no-go recommendation with data
How we measure
  • Accuracy vs. expert-labeled ground truth
  • Time saved, measured against current SOP
  • Failure modes — categorized, not hidden
  • Cost envelope including review overhead

Stage 03 · 8–12 weeks

Production system

We build the pilot as a real internal system: auth, role-based access, full audit logs, human-in-the-loop gates, cost caps, fallbacks, and observability. Delivered with runbooks your engineers can operate — we're not trying to be a dependency.

Outputs

  • Production-grade system in your cloud
  • SSO, RBAC, audit trail, retention policy
  • Observability dashboards + alerting
  • Runbooks + operator training
Stack agnostic
  • Model providers: Anthropic, OpenAI, Azure, Bedrock
  • Cloud: AWS, GCP, Azure, on-prem where needed
  • Auth: your existing IdP (Okta, Entra, etc.)
  • Data: stays where your policy says it stays

Stage 04 · Ongoing

Governance & scale

Once you have one system shipped, the question becomes: how do we do this repeatably, safely, and at a pace the board can see? We build the program — AI policy, model-choice rubric, review cadence, and the portfolio view that keeps every workflow in flight legible.

Outputs

  • AI usage policy, reviewed by counsel
  • Model-choice rubric (when to use what)
  • Quarterly portfolio review, written for the board
  • New-workflow intake & triage process
Industries we work in
  • Pharma & biotech — regulatory affairs, clinical ops
  • Financial services — KYC/AML, credit memos, research
  • Legal — contract triage, discovery, memo drafting
  • Professional services — proposal drafting, research synthesis

Let's talk

Start with a 30-minute call.

We'll walk through one workflow you've been trying to improve, and leave you with a concrete view of what a pilot would look like — whether you hire us or not.

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