See What FDD AI Can Do

What can more than a decade of Item 20 data tell us about franchise system performance?

FDD AI combined Item 20 outlet data across thousands of FDDs to construct a year-by-year analysis from 2013 through 2025, examining openings, terminations, non-renewals, transfers and other closures. The research also examines industry differences and identifies unusual periods in the historical data.

How often do franchisors provide an Item 19 Financial Performance Representation – and what kinds of financial information do they disclose?

FDD AI analyzed more than 15,000 FDDs to measure the prevalence of Item 19 disclosures, compare different types of FPRs and examine how disclosure practices have changed over time.

Could FDD data be used as an initial financial-risk screen for lenders, investors and other professionals?

FDD AI examined 2025 and 2026 FDDs to identify franchisors whose auditors raised going-concern doubts. The analysis identifies the affected brands, considers their system size and explains why a going-concern opinion may warrant additional investigation.

Suppose a board or investment group wanted to identify current food-franchise opportunities within a specific investment range.

FDD AI screened current 2025 and 2026 FDDs using Item 7 investment information and Item 20 outlet data to identify food-sector concepts with a disclosed maximum initial investment of $200,000 or less. It then organized the findings as a board-level research memorandum.

FDD AI analyzed current 2025 and 2026 FDDs across a broad definition of home services – including cleaning, restoration, home improvement, plumbing/HVAC, lawn and landscape, moving and storage, security, and real estate/property services – to identify and compare the largest systems by outlet count.

Item 3 can contain valuable information about disputes involving a franchise system – but comparing litigation activity across hundreds or thousands of brands manually would be extremely difficult.

FDD AI analyzed Item 3 litigation information to identify franchisors appearing most frequently as the initiating party, while also examining the underlying disclosures and identifying important limitations in how the data should be interpreted.

How do important franchise agreement provisions vary across industries?

FDD AI examined current FDDs to compare arbitration and litigation-based dispute resolution, personal guarantees and post-termination noncompetes across franchise industries. Where a provision – such as jury-trial waivers – is not available as a discretely coded field, the research identifies illustrative examples from the underlying text rather than presenting an unsupported corpus-wide percentage.

How can FDD data help someone compare competing franchise opportunities within a specific industry?

FDD AI identified 19 painting franchise systems and analyzed available Item 20 performance data, litigation and bankruptcy disclosures, initial investment requirements and Item 19 financial performance information. The research compares the brands from multiple perspectives, including historical system performance, capital requirements and disclosed revenue potential.