Compliance
Intelligence.
Deterministic checks first. Generative synthesis second. Speed up policy and QA reviews while keeping evidence and human judgment visible.
Philosophy: Rules-first, AI second.
LLMs are probabilistic and prone to hallucination. When evaluating high-stakes compliance, teams need more than a plausible answer. We build systems that extract structured data, pass clear requirements through deterministic rule engines, and reserve AI for classification, summarization, and ambiguity support.
Engine Capabilities
Deterministic Checks
Translate clear requirements into logic gates such as thresholds, required fields, and pass/fail conditions that can be evaluated consistently.
Evidence Capture
Every compliance decision is packaged with the exact paragraph, image, or table cell used to justify the pass/fail state.
Jurisdiction Awareness
Code requirements shift by geography and project phase. The engine can route reviews based on jurisdiction, metadata, and policy scope.
Risk Scoring
Flag edge cases for human review and prioritize reviewer attention where inputs are incomplete, ambiguous, or outside known rules.
Deployment
- Local/VPC ExecutionProcess sensitive citizen data, PII, and proprietary designs entirely behind your existing firewall.
- Redaction ProxiesIf utilizing cloud intelligence, automatically strip sensitive entities locally before transmitting context to external models.
Supported Workflows
Municipal Policy Review
Ingest application packages, compare them against local requirements, and create reviewable decision records for staff and applicants.
Internal Procedure Audits
Scan internal communications, action logs, or purchasing requests to determine compliance against corporate governance rules natively.
Engineering QA Gates
Establish automated checks on preliminary drawings and specifications to ensure they meet the master contract requirements before human review.
Stop rubber-stamping.
Reduce review friction with evidence-backed evaluation pipelines and clear escalation paths.