Mechanisms of Intelligence

Senior ML engineering, on demand.

Production AI for early-stage teams — Claude integration, eval harness, monitoring, the full production stack — at a price you can read on the page.

  • Fixed price
  • 6-week audit
  • ~30-page scored report
  • Philadelphia, PA

What you get

Three pillars, scored on evidence.

01 / Pillar

Data Architecture

We trace your data from raw source to live model. You learn which link breaks first under production load — and how to fix it before it does.

02 / Pillar

Access Control

We map who can touch your model, weights, training data, and inference endpoints. You get the list of gaps that turn into incidents — ranked by what regulators and attackers find first.

03 / Pillar

Process Documentation

We pressure-test your runbooks, on-call rotations, and kill switches against real failure modes. If they would fail at 2 AM, you find out now — not then.

How the audit runs

Six weeks, evidence cited line by line.

  1. IntakeWeek 1

    We sign the NDA, agree on what is in scope, and send the document request. You name the stakeholders.

  2. Evidence ReviewWeeks 2–3

    We read everything. Architecture docs, access policies, pipelines, runbooks. We trace what actually happens, not what the docs claim.

  3. Pillar ScoringWeek 4

    Each pillar gets a score from 1 to 4 with the evidence cited line by line. Disagree with a score and you can challenge it on the merits.

  4. ReportWeek 5

    A ~30-page written report you can hand to your board. Findings, risks, and a ranked list of what to fix first.

  5. DebriefWeek 6

    A 60-minute walkthrough with your stakeholders. Then a 30-day check-in to see what moved.

Ready to evaluate your AI deployment readiness?

Philadelphia, PA · AI readiness audits for companies deploying AI where failure has consequences.