Mechanisms of Intelligence
Production AI, shipped this week.
Senior ML engineering for early-stage teams — Claude integration, eval harness, monitoring, the full production stack — at a price you can read on the page.
What you get
Three pillars, scored on evidence.
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.
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.
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.
- 01
Intake — Week 1
We sign the NDA, agree on what is in scope, and send the document request. You name the stakeholders.
- 02
Evidence Review — Weeks 2–3
We read everything. Architecture docs, access policies, pipelines, runbooks. We trace what actually happens, not what the docs claim.
- 03
Pillar Scoring — Week 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.
- 04
Report — Week 5
A ~30-page written report you can hand to your board. Findings, risks, and a ranked list of what to fix first.
- 05
Debrief — Week 6
A 60-minute walkthrough with your stakeholders. Then a 30-day check-in to see what moved.
Free tools
No payment. No account.
The Knowledge Base
A live, browsable snapshot of an AI research knowledge base — continuously crawled across arXiv, the major frontier labs, Hugging Face, and Hacker News. Embedded, clustered, and rendered as a navigable semantic map.
Open toolThe Readiness Scan
A three-minute structured scan of your AI deployment posture. Returns a scored topology across four governance pillars, mapped to the major regulatory frameworks.
Open toolCommission an audit
A scored, written assessment of your AI deployment readiness — data architecture, access control, and process documentation.
Start an auditRead our writing
Technical writing on AI readiness, deployment risk, and the methodology behind our scoring model.
Browse essaysReady to evaluate your AI deployment readiness?
Philadelphia, PA · AI readiness audits for companies deploying AI where failure has consequences.