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arXiv cs.AI
6/10

PolicyGraph

An ontology-learning app for compliance and legal-ops teams that turns a stack of policy PDFs into a navigable graph of obligations, exceptions, and definitions.

Target user

compliance officers at mid-size companies drowning in policy and regulatory documents

Features
  • Upload a folder of policies/regulations and get a structured graph of terms, obligations, and exceptions
  • Cross-document conflict detection ("Policy A says X; Regulation B says not-X in these cases")
  • Plain-English summary of any node in the graph for non-lawyer stakeholders
  • Audit trail showing which source paragraph every extracted claim came from
Why now

OntoLearner proves the underlying ontology-learning pipeline is finally cross-domain and reproducible — the missing piece for a real compliance product rather than a research demo.

Signals · overall 6/10
Demand
7/10

Compliance teams explicitly report drowning in regulatory paperwork and document review; White & Case 2025 benchmarking survey and KPMG 2025 both cite manual document review as the top pain point LLM tooling can solve.Artificial intelligence in the compliance functionCompliance Automation: How to Stop Drowning in Regulatory Paperwork

Whitespace
5/10

GRC space is crowded (Vanta, Drata, LogicGate, NAVEX PolicyTech, OneTrust, ServiceNow GRC) but ontology/graph-of-obligations as a first-class UI is niche — only small players like ComplyOne are explicitly building W3C OWL compliance knowledge graphs.Best GRC & Policy Management Software 2026: Comparison - KurumsWhy We Built a Compliance Ontology Using W3C OWL and SPARQL

Monetization
7/10

Proven B2B willingness to pay — policy management software market is $1.97B in 2024 growing ~9-12% CAGR; Vanta/Drata/LogicGate price in the $10k-$50k+/yr range and incumbents are clearly monetizing automation features.Policy Management Software Market Size, Share & Forecast 2032Best GRC & Policy Management Software 2026: Comparison - Kurums

Longevity
8/10

Regulatory volume keeps growing and compliance is mandatory and budget-protected; AI-driven compliance transformation is a multi-year secular shift, not a fad.How AI is poised to reshape compliance functions (KPMG 2025)

Feasibility
5/10

OntoLearner plus mature graph stores (Neo4j, Apache Jena) make the core pipeline buildable, but the navigable graph UX, exception/conflict handling, and ongoing ontology maintenance against changing regs is non-trivial for a small team.Ontological Memory for Compliance: Turning Regulations into Executable Knowledge

OntoLearner: A Modular Python Library for Ontology Learning with Large Language ModelsarXiv cs.AI · 2026-07-04 (21d ago)