
TridenGuard is a deterministic validation system for LLM outputs in legal and financial contracts. It addresses a critical gap in enterprise AI adoption: LLMs hallucinate, but contracts don't forgive. The system enforces a neuro-symbolic isolation architecture. First, Lobster Trap (Veea) blocks prompt injections, PII leaks, and data exfiltration at the ingress layer. Second, a local Phi-4-mini model extracts 8 atomic radicals: Actor, Deontic, Action, Object, Temporal, Spatial, Metric, and Condition. Third, a deterministic validator applies 8 exclusion rules (R1-R8) and a grounding check that verifies every radical exists literally in the source text. If a structural failure is detected — for example, an orphan metric without an actor — the case is quarantined in a forensic panel. A human lawyer reviews the case, approves or discards it, and that decision becomes training data for a sovereign local LoRA model. The system also exports audit reports in CSV for regulatory compliance. TridenGuard is designed to run on Veea Edge Nodes: low-latency, air-gapped, and fully sovereign. No cloud. No data leakage. The enterprise owns its intelligence. Benchmark results (Phase 1, 20 cases): 100% block rate for prompt injections and PII, 100% interception of real-world court hallucinations (Lacey v. State Farm, Russell v. Mells, Lexos Media, Baidu AI), 87.5% structural validator accuracy, and 85% overall pipeline accuracy. A 64-case benchmark matrix is designed for V2. Roadmap: V2 adds TOON + GBNF token-level governance and Fisher's Exact Test for statistical threat hunting. V3 adds sovereign local LoRA fine-tuning from human decisions. Built for Veea Edge Nodes.
19 May 2026