A local, agentic AI pipeline that analyzes tabular data, detects anomalies, and generates interpretive summaries using local LLMs orchestrated via the Model Context Protocol.
Enables AI agents to sign decisions with post-quantum cryptographic proofs and maintain secure audit trails for compliance. It provides tools for stamping events, verifying chain integrity, and exporting audit data across industries like finance and healthcare.
Enables AI agents to investigate Splunk exports or live queries using deterministic detectors and an iterative analysis loop, all running locally without data leaving the machine.
Enables AI agents to maintain persistent, local memory with retrieval-augmented search, knowledge graphs, and context surfacing, without any cloud dependencies.