Solution
HalluCase benchmarks models against known failure modes. MCP-Law enforces domain safety rules at the protocol level.
The problem
A hallucinated citation can get a firm sanctioned. A misstated legal standard can corrupt an entire analysis. General-purpose AI benchmarks do not measure the failure modes that matter in high-stakes domains — citation fabrication, statutory misreading, jurisdiction confusion. Teams deploying AI in consequential settings have no standard way to test whether their model is safe to use.
How it works
HalluCase benchmark: the first dataset built specifically for hallucination detection in high-stakes domains. Covers citation fabrication, statutory misstatement, and reasoning errors across multiple jurisdictions.
Evaluate models on citation accuracy, statutory reasoning, and jurisdiction compliance with structured scoring.
MCP-Law servers enforce safety policies at the infrastructure layer — not a post-hoc filter, but a protocol-level constraint.
Generate safety reports suitable for regulator submission and client review without manual redaction.
Continuous monitoring: regression detection across model updates so a new version does not introduce failures the old one did not have.