The regulatory systems your work depends on — statutes, codes, frameworks, rules — are real, physical things that connect in specific ways. DivideGraph builds exact digital replicas of those systems, anchored in the source, so you always know where you stand.
Two GARI deployments built on the same graph-intelligence engine. Different regulatory domains, same anchored-in-the-source method.
Chaffee County parcels, title chains, DWR water rights and water court decrees, CCLUC zoning, municipal codes, FinCEN CTA / Real Estate Rule, governance records, campaign finance, and entity networks — modeled as one queryable graph for title companies, developers, attorneys, brokers, and county staff.
Customer sign in → Request Access →NIST, FFIEC, DORA, and AI governance frameworks modeled as a graph so examiners' questions get answered with a citation, not a guess. Built for community banks operating under increasing compliance pressure.
Customer sign in → Request Access →Examiners — bank, county, water-court, FinCEN — work from a known set of frameworks. We model those frameworks as a graph anchored in the source, so you can see where your program stands before the examiner does.
We've read the frameworks so you don't have to — NIST and FFIEC for banks; CRS, CCLUC, and DWR rules for land use. Ask a plain-English question, get a plain-English answer backed by the actual source.
When an examiner asks why you made a decision, you'll have a direct citation — not a chatbot's best guess. DivideGraph never tells you something it can't prove.
Examiners — bank, county, water-court, FinCEN — work from known frameworks. DivideGraph is built from those same frameworks, so you can see where your program needs work before exam day, not during it.
Regulators are already asking about AI governance — for banks and for property data. DivideGraph gives you a clear, plain-English path through AI risk requirements, anchored to the actual rules.