Institutional access to franchise market intelligence
ChainAI is a structured data and signal layer for the franchise market. We normalize Franchise Disclosure Documents at scale and combine them with real demand signals from active buyers.
Built for private equity, family offices, and multi-unit operators who want a systematic way to source, screen, and monitor franchise opportunities.
Why this matters
The franchise market is large, fragmented, and poorly instrumented.
- Move beyond anecdotal deal flow by working with normalized, comparable data across brands and years
- Identify under-the-radar concepts using disclosed economics and observed buyer interest
- Monitor portfolio exposure as new FDDs are filed and systems evolve
What you get access to
Institutional access is tailored, but typically includes:
- Structured FDD data across Items 5, 6, 7, and 19, normalized across brands and years
- Clean investment ranges, fees, unit counts, closures, and disclosed performance metrics
- Aggregated, anonymized demand signals derived from buyer activity on the Franchise Explorer
- Periodic data exports or private API access, depending on use case
We do not provide investment recommendations. We provide infrastructure.
Example institutional use cases
- Sourcing: Screen hundreds of brands by capital requirements, fee structure, system growth, and observed demand
- Diligence support: Benchmark disclosed economics and unit dynamics against peers and category medians
- Portfolio monitoring: Track new FDD filings, fee changes, unit growth, and demand shifts for owned and competing brands
How the data is built
ChainAI combines rule-based extraction with large language models to map FDDs into a consistent schema.
- Canonical brand identifiers across filings, years, and jurisdictions
- Versioned historical records to enable longitudinal analysis
- Alignment between legal disclosures and platform-level behavior signals
This is designed as an input layer for your own analytical workflow.
Talk to us about institutional access
Share a few details about your team and what you are looking for. We will follow up with a short data overview and example output.