PathReader turns your policy documents into deterministic, auditable enforcement rules for AI agents. Unlike LLM-based guardrails, PathReader evaluations are reproducible: every allow/block/escalate decision traces directly to a specific rule and source document. A compliance auditor can follow the trail. No probabilities. No black boxes. How it works: Upload your policy PDFs → PathReader extracts and structures the rules using AI → your team reviews and approves each rule with its source quote → publish a versioned policy set → evaluate any agent action in real time. Every decision returned includes the rule that triggered it, the source document, and the evaluation trace. That's the audit record. Built for regulated industries: Insurance, healthcare, finance, legal — anywhere AI agents take consequential actions and "probably compliant" isn't acceptable. We're in early development and working with design partners. Contact: hello@pathreader.ai
| Employees | 2 (1 on RocketReach) |
| Founded | 2026 |
| Industry | Software Development |
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Christopher Fiorelli is the Co-Founder and CTO of PathReader AI.
1 people are employed at PathReader AI.
PathReader AI is based in Seattle, Washington.