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, and 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.