Flypower

Flypower — Jurisdiction-level social and political risk dataset for energy and data-centre siting: for each county or locality, a structured record of which officials decide (planning commissioners and council members) with their voting patterns, mapped opposition organisations and their campaigns, stakeholder profiles, threshold conditions that determine approval, local media and social-media sentiment, regulatory filings, land-use plans, hearing minutes and zoning changes — condensed into a four-tier path-to-approval verdict (Clear, Monitor, Friction, Kill) with ongoing monitoring of votes,…

Flypower offers (Alternative, Sentiment, Geospatial, ESG) — 400-plus projects analysed is the vendor's own stated coverage figure, spanning solar, wind, battery storage and data centres nationwide. Each due-diligence engagement produces 50-70 pages of structured analysis, so the accumulated corpus implies tens of thousands of pages of jurisdiction-level assessment — roughly 20,000-28,000 pages at the stated report length — each carrying stakeholder maps, official voting records, opposition inventories and threshold conditions. Underlying harvested material is far larger, covering government meetings, social media, news, regulatory filings and land-use plans per jurisdiction, but the structured extractable layer is bounded by the 400-project figure.

Pricing community and political risk in project underwriting, which the vendor explicitly frames as an unpriced balance-sheet risk for capital partners; siting screens that exclude jurisdictions where approval is structurally blocked; entitlement-probability and timeline models using validated historical verdicts as training targets; opposition-anticipation and engagement-strategy models; portfolio-level regulatory-risk aggregation for infrastructure funds and lenders; event-study features on political and electoral cycles for energy-equity strategies; and a rare human-validated labelled corpus of local government decisions on energy infrastructure for training predictive models

The data is with 2 years of history.

Coverage spans US; Application Software, Electric Utilities; alternative, sentiment, geospatial, ESG; equities, fixed_income.