Questions die in email chains, meetings, and hallway asks. Middle management becomes a telephone game. Knowledge is trapped in individuals. Seshe's routing intelligence watches how questions flow, learns who actually solves them, and progressively takes over the routing.
Organizational Knowledge Has a Routing Problem
Three Phases: Watch, Suggest, Route
The system starts in pure observation mode. No configuration, no domain setup, no expertise tagging. It learns YOUR organization.
The AI observes (Phase 2A)
Every completed question chain teaches the system. Who asked? Who forwarded? Who actually answered? The AI builds a routing graph — a map of how expertise flows through your organization. Question clusters emerge organically from real usage, not from preconfigured categories. (99 tests)
The AI recommends (Phases 2B-2C)
After enough data, the AI starts suggesting who to route questions to. It shows confidence scores and reasons. Every acceptance, override, and redirect teaches the system via the feedback handler. Multi-route detection handles compound questions with fan-out orchestration. (104 + 154 = 258 tests)
The AI decides (Phases 2D-2E)
When confidence exceeds 75%, the AI routes autonomously — no human decision needed. Per-company config controls thresholds and NQE auto-execution. Organic expertise tracking and personnel lifecycle adapters handle role changes and departures automatically. Cross-pollination discovers new expertise paths. (101 + 120 = 221 tests)
See How the AI Adapts
The same question, handled differently based on system maturity. Switch between confidence levels to see the AI's behavior evolve.
Four Learning Signals
The system learns from formal routing decisions AND organic conversations. No explicit training required.
User accepts the AI's routing suggestion. The graph strengthens that routing path.
User picks someone different. The AI analyzes why and adjusts — overrides teach more than acceptances.
Recipient says "not me, try Ben." The strongest learning signal — the AI immediately reroutes and remembers.
People chatting in threads. The AI passively extracts expertise signals — the lowest-friction, highest-volume source.
Handles Your Org's Lifecycle
People join, leave, change roles, and teams restructure. The routing intelligence adapts automatically.
Starts with zero routing weight. System increases exploration ratio for their team's clusters. Within 2-4 weeks, the graph learns what they resolve.
AI identifies the closest backup for each question type. Exploration spikes temporarily. New routing paths stabilize within 2-4 weeks.
Old expertise decays naturally via temporal decay. New expertise builds as they answer different question types. Transition is gradual.
Routing edges are person-to-person, not position-to-position. They survive restructures. The system discovers new cross-team paths.
Unlike systems with hardcoded expertise domains, Seshe discovers YOUR organization's topics from real usage. No configuration, no domain setup.
Seshe routes to the right person. Conduit pulls the right data. The AI combines both into one complete answer. This is what enterprise intelligence looks like.
Routes to the right expert based on learned patterns. Skips unnecessary layers.
Queries production data across all systems in natural language. No data movement.
Expert interpretation + machine data = complete, data-backed answers in minutes.
See how routing intelligence transforms your organization's knowledge flow. Get a personalized demo.