A hybrid inference engine fusing specialized Deep Learning (DL) models—specifically fine-tuned Legal-BERT architectures for deterministic structured extraction—with LLMs for deep semantic reasoning.
A highly specialized multi-staged DL pipeline built for legal due diligence. It fuses fine-tuned DL BERT architectures operating on proprietary legal datasets for structured extraction, alongside LLMs for natural language reasoning.
Powered by a Multi-Task Legal-BERT DL model fine-tuned to simultaneously classify clause types and compute statistical risk liability.
Runs an Unfairness Detection DL BERT to strictly isolate asymmetric and commercially unviable obligations.
Using a specialized Legal-NER DL Model to extract high-risk parties, temporal variables, and fiscal constraints.
Offloads complex subtext analysis and missing assertion detection to a LLM