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plaso

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Yomi is engineered to operate on a fundamentally faster timeline. By orchestrating SANS SIFT Workstation forensic tools through a strict, type-safe Model Context Protocol (MCP) server and evaluating evidence via a cascading Epistemic Doubt Engine, Yomi achieves a Time-to-Containment (TTC) of < 5 seconds.

  • Updated Nov 5, 2026
  • Python

An AI-assisted DFIR tool designed to tame the timeline deluge. It leverages ML to triage anomalies and local LLMs to reconstruct high-level events, allowing investigators to query evidence with strict forensic soundness and 100% traceability to the source artifacts.

  • Updated Jun 16, 2026

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