Expert Interview Engine
Voice, chat, and document-aware conversations that feel like focused interviews, not forms. Adapts to how the expert actually thinks about the work.
Expertise Mining
From people to data.
Extract the judgment, decision logic, exceptions, and tool habits your top performers carry, and turn them into machine-readable expertise that agents and teams can use.
Documents do not contain the expertise that runs the company.
Process maps describe steps. Wikis describe policies. Tickets describe outcomes. None of them describe the judgment behind a decision: the exceptions an expert recognises in two seconds, the sources they actually trust, the field they always double-check, the moment they escalate.
Without that layer captured, every AI initiative spends months trying to teach systems what experienced people already know. Verti's first sold product is the layer that fixes it: a structured expertise package extracted from the people who hold it.
See an expertise mining session
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How Expertise Mining works
Six structured stages take one selected expertise from a person's head into a validated, agent-ready package, in about a day, not months.
Select the expertise
Mine the expertise inside the role, not the role itself: pick one high-impact capability (quote review, claims triage, compliance check, customer escalation) based on frequency, judgment density, and business outcome value.
Conduct structured conversations
Run focused, interview-style sessions with the experts using voice, documents, case walkthroughs, and real examples, with coverage tracking that always knows the next gap to fill.
Extract the operating knowledge
Capture decisions, exception patterns, trusted and untrusted data sources, tools, handoff points, escalation conditions, and output quality standards.
Build the expertise package
Turn what was captured into a machine-readable package: operations, decision logic clusters, exception library, source inventory, approval paths, and output standards.
Generate the Agent Design Blueprint
Translate the expertise into agent design inputs: candidate agent responsibilities, required context and tools, action boundaries, handoff and approval rules, and evaluation scenarios.
Validate and approve
Route the package through expertise admins for review and sign-off before it becomes canonical operating knowledge for agents or teams.
What an expertise package contains
Durable artifacts, not transcripts, not slides, not generic process maps.
- Expertise definition & business outcome
- Complete operation map
- Decision logic clusters
- Exception & edge case library
- Trusted source inventory
- Tool & system usage
- Handoff & approval points
- Output quality standards
- AI Readiness assessment
- Agent Design Blueprint
- Evidence-backed validation
Capabilities
Six engines run underneath every mining session.
Decision Logic Extraction
Identifies and maps the judgment, conditions, and reasoning behind expert actions, turning intuition into reusable logic.
Exception Pattern Library
Captures edge cases, conditional paths, and special circumstances that change normal workflows, the part wikis always miss.
Source & Tool Inventory
Documents which data sources experts trust, which fields matter, and which tools they actually use to make each decision.
Expertise Validation Workflow
Routes mined expertise through human review and admin approval before it ever becomes canonical operating knowledge.
Agent Design Blueprint
Translates the expertise package into agent design inputs: responsibilities, context needs, boundaries, and evaluation scenarios an agent team can be built from.
Why this is different
Not a transcript or document
Output is a machine-readable expertise package. Agents and operations can use it directly, not a recording that still has to be interpreted.
Judgment-first, not task-first
Captures decision logic and expert reasoning (the conditions that change behaviour), not just the ordered list of steps.
Governance-ready by default
Expertise admins approve packages before they become production operating knowledge; there is no quiet shortcut into agent behaviour.
Designed to stay current
Packages are versioned and refresh-friendly, ready for the Continuous Learning System to detect drift and propose updates.
See Verti run on your operations.
Verti connects expert judgment, live context, governed action, and learning loops into one production system.