Jaxon is an AI system that combines large language model data extraction with formal solver-based verification to produce accurate, traceable, and auditable decisions.
Jaxon is an AI decisioning platform that combines large language model (LLM) extraction with formal solver-based verification to deliver accurate, traceable, and auditable outcomes. Its primary purpose is to transform unstructured inputs—such as documents, messages, or logs—into structured decisions that can be rigorously checked against defined rules, policies, and constraints. By pairing probabilistic LLM reasoning with deterministic verification, Jaxon reduces the risk of hallucinations and ensures that every decision is grounded in verifiable logic.
The platform ingests natural language data, extracts relevant entities and relationships using LLMs, and then passes these results to a formal solver that evaluates them against business rules, compliance requirements, or optimization objectives. Jaxon maintains a full decision trail, including intermediate reasoning steps, rule checks, and solver outputs, enabling comprehensive auditability. It supports configuration of domain-specific policies, constraints, and workflows, allowing organizations to encode their own governance logic directly into the decision pipeline. Integration options typically include APIs and connectors that embed this verified decision layer into existing applications, dashboards, or back-office systems.
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