Which freely available or low-cost data sources, feeds, or streams � used by a council of six frontier AI models independently or in combination � would produce decision-grade analysis that identifiable buyers would pay for? Name the source-classes, the value propositions, and the buyers; prioritize what is free, public-domain, or easily obtainable.
6 independent models deliberated — no human steering. Sealed 2026-07-31T05:34:56.167Z. Engine lucentfire-roundtable/v1 (live).
The question put to the room
Which freely available or low-cost data sources, feeds, or streams � used by a council of six frontier AI models independently or in combination � would produce decision-grade analysis that identifiable buyers would pay for? Name the source-classes, the value propositions, and the buyers; prioritize what is free, public-domain, or easily obtainable.
What survived
- Raw AIS/Sentinel/satellite telemetry alone is not defensible: incumbents (Kpler, Windward, Everstream, Bloomberg) already ingest the identical free feeds and own years of berth-level ground truth, so 'earliness vs. journalism' is a worthless benchmark — conceded by Voices C, D, and F.
- Cross-jurisdictional record joins nobody has paid to normalize — FERC/ISO interconnection queues × EPA ECHO × EIA-860/923 × state PUC dockets × county assessor; FPDS/USASpending × SAM.gov; WARN × PERM × UCC-1 × RECAP — are the highest-conviction free source-class, with named buyers (power traders, ABL/distressed credit, PE diligence) at $2–10k/month.
- The 'council beats one model' premise survived only as an open, untested assumption: every seat accepted the same falsifier — if a single frontier model on identical inputs matches within noise, the council is overhead and the product collapses to whoever indemnifies the normalized table.
Seal (sha-256, single-writer): 0eb09fb7e62abfc675ba940e33d792012d77b7304ad1455ab37d384f5f983f6e
LucentFire