Mentiko encodes how senior professionals think — not what they wrote down — and deploys it as AI that decides the way they would. At scale. With full explainability.
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This is tacit knowledge — judgment built from thousands of decisions, impossible to document in a manual, lost when the expert leaves.
“JPMorgan does not take the same decisions as Wells Fargo. Same data. Same regulations. Different judgment. That institutional judgment is uncodified — until now.”
Three stages that turn decades of accumulated expert judgment into a deployable, explainable AI system.
The platform interviews your experts through adaptive sessions designed to extract tacit knowledge. Not what they can write in a manual — the pattern recognition, the red flags, the intuitions that come from 10,000 cases. The AI probes through scenarios, hypotheticals, and disagreements to surface knowledge the expert can't articulate directly.
Expert judgment is encoded as a structured, evolving model — not a static document. Principles, decision rules, confidence hierarchies, contextual exceptions, and known blind spots. The profile grows with every interaction. It compounds.
Encoded judgment is deployed to new cases in production. Every decision includes full explainability — which principles were applied, why, and with what confidence. Your senior expert's judgment, applied consistently across the organization, 24/7.
The cost is the same.
Your best credit analyst retires next year. She's rejected loans the models approved — and been right every time. Her judgment lives in pattern recognition built across 3,000 cases: revenue seasonality signals, sector-specific red flags, behavioral tells in third-time borrowers. Your documentation captures her process. It doesn't capture her intuition. Every month she's gone, the portfolio takes decisions she wouldn't have approved.
Your senior radiologist catches what the AI-assisted screening misses — a shadow density pattern in a specific location that she's seen turn malignant in 200 prior cases. It's not in any diagnostic manual. Your junior staff follows the protocols perfectly and still misses it. When she's on vacation, the follow-up rate drops. When she retires, it drops permanently. The institutional knowledge isn't in the protocols — it's in her.
Your litigation partner knows which arguments land with which judges in which jurisdictions. She reads a contract and flags the three clauses that will cause problems in 18 months — not because a checklist told her, but because she's seen those patterns play out across 200 cases. Two associates with identical credentials, reviewing the same document, miss it. That gap is 20 years of judgment. It's not transferable in a mentorship program.
Your senior physiotherapist sees 8 patients a day. Her encoded judgment powers assessments for 800. New service lines. Subscription models. Revenue expansion without more square meters or headcount.
Your junior analyst scores a 3 on qualitative risk sensing. The senior standard is 7. The platform identifies the exact gap and prescribes the cases that close it. Not “shadow the senior for 6 months.” Surgical, measurable development.
Compare every junior decision against your encoded senior standard. Catch divergence before it becomes a costly mistake. Continuous quality monitoring with audit-ready explainability on every call.
The replacement doesn't start from zero. They start from the previous expert's encoded judgment as a baseline, then layer their own on top. Ramp-up goes from 12 months to weeks. The judgment stays, evolves, and compounds — even after the expert is gone.
Our architecture is grounded in peer-reviewed research from the institutions defining the frontier of AI preference learning and knowledge representation.
