Governance, compression, and visibility for organizations that cannot afford guesswork.
Pink House builds the control points that live inside the architecture — before the output leaves the system, before the tokens burn the budget, and before the bill becomes the news.
Pre-execution AI governance. The control point before the output leaves the system.
Regulated AI needs more than logs after the fact. Michelangelo enforces admissibility at runtime — before an output can be used — and seals machine-readable evidence packs that can be replayed. Mapped to FDA 21 CFR Part 11 and EU GMP Annex 11. Built for high-consequence workflows including cleanroom environmental monitoring, deviations, and batch-release support. Provisional patent 63/924,367.
AI wire compression — fewer tokens in, same answer out.
Raquel compresses language-aware payloads before they hit the tokenizer. Not gzip. Content-aware encoding that cuts inbound token load so providers and customers keep margin without changing the end-user experience.
Real-time AI cost and session monitoring across the providers you actually use.
You cannot govern what you cannot see. TokenScope watches spend and sessions provider by provider — starting with the top active providers — so finance and engineering share one picture.
Shipping August 15, 2026
Six chapters. From Markov chains to Tuesday’s real threats.
A series for readers who want to understand how we got here — not just react to headlines.
Business and AI pieces from the writing portfolio.
Mid-2026 population data — how big generative AI actually is, with citations. Also on LinkedIn.
Graham’s number, odd/even traps, and where models start bluffing.
When flattery burns tokens — and the bill spikes 67%.
Why output errors are a governance failure, not a model failure.
Why AI memory constraints matter more than most users realize.
Thinking partners, then and now — including serious work with AI.
Forensic analysis made clear enough for people to act on.
Not everything here is a white paper. If you want a short story:
The Useful Mission — three characters, a boat, Frying Pan Shoals, 1962.
Pink House Technology builds practical control points for AI at work — governance before the output leaves the system, compression before tokens burn the budget, and visibility across the providers you actually use.
Phil Cheevers founded Pink House to close the gap between “we use AI” and “we can defend, measure, and afford how we use AI.” The work sits with regulated operations, builders, and teams who need instruments — not slogans.
Best for: partnerships, regulated QA, compression pilots, TokenScope early access