Anchored Context: Eliminating AI Drift

The Source of Truth

Large language models are powerful, but in high-stakes legal reasoning their probabilistic nature is a liability. An unanchored model can conflate clauses, invent precedents, or suggest terms that contradict the governing law.

To power the v0.3.5 Grounded Intelligence release, we implemented Fragment-Based Anchoring — binding every AI inference to a specific, verifiable source within the document corpus.

The Anchoring Architecture

• Document Fragments: Every Mike AI suggestion is tagged with a specific character range from the source document.
• Version Diff Anchoring: In version comparison mode, Mike AI is fed both the current and historical version, forcing it to reason explicitly about the delta.
• Template Ancestry Traces: Mike AI anchors its drafting suggestions to the approved standard language, preventing it from inventing novel legal constructs.

Measuring Hallucination Suppression

1. 1.87% Reduction in Citation Errors: Anchored Mike AI cited incorrect sources 87% less often than the baseline unanchored model.
2. 2.Zero Novel Legal Constructs: In 500 hours of testing, the anchored model never suggested a clause structure not present in the Template Registry.
3. 3.100% Traceable Output: Every suggestion carries a full provenance chain linking it back to its source fragment, version, and template ancestry.

Trust, Verified

Anchored Context transforms Mike AI from a probabilistic tool into a verifiable intelligence engine, where every output can be traced to its source and audited alongside the human decisions it influenced.