Case study · Media & Production
A high-end Los Angeles commercial production company was rebuilding every bid from scratch — the real cost intelligence lived in one producer’s head. We’re building an AI system that runs on the studio’s own numbers, so each bid starts sharper than the last.
In production, the margin is made or lost in the bid — and the intelligence that makes a bid accurate (what a two-day shoot with three principals really costs, in this studio’s market, with these vendors) lived in one producer’s experience. Fast, but not transferable, and not compounding. We’re changing where that knowledge lives.
A two-layer AI operating system for the studio, adapted from the same architecture we run our own firm on — a permanent context layer that remembers the business, and an active work layer that does the job against it.
The tenth bid should be smarter than the first.
This is an active engagement, built session by session on the studio’s own machine — the producer owns and operates the system, we guide the build. As real jobs run through it, the context layer learns what work actually costs in their numbers, with their vendors, in their market. The results become the studio’s to report; we’ll publish them here once the engagement clears.
The whole system — the context layer, the bid engine, the workflows — running in-house on your own data. Not a tool you rent; an intelligence asset that compounds with every job you run.
Anonymized at the client’s request while the engagement is in progress. A production-industry reference implementation.
The engagement behind this case: CompanyOS → · back to selected work →
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