How Evnao works

The Engine Behind Semantic Support.

Evnao combines Gemini generation, PostgreSQL full-text and vector retrieval, durable tickets, provider integrations, and explicit AI/human conversation state.

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System foundations

A small number of explicit boundaries.

Architecture language on this page describes implemented application behavior, not a proprietary or independently audited invention.

Semantic Intent Routing

Evnao combines PostgreSQL full-text and vector retrieval with recent conversation context to find relevant published knowledge for a reply.

Generative UI Rendering

The widget can render interaction cards, but external results are treated as examples unless a connected tool returns the underlying data or confirms the action.

Isolated Knowledge RAG

Knowledge chunks are scoped by team and publication state. Retrieval combines full-text and vector candidates; the model can still be wrong, so handoff and review remain necessary.

The Paradigm Shift

From a customer message to a controlled reply.

Evnao workspace

Illustrative product flow

Incoming · Supported channel

A customer asks a business-specific question.

Tenant-scoped processing

Handles varied phrasing through retrieval and model generation.
Maintains conversation context across topic changes.
Indexes supported sources through visible background jobs.

Visible outcome

A grounded reply or clear escalation.
Durable conversation and audit state.
Provider errors remain recoverable.

View in the workspace

Legacy Decision Trees

Requires rigid "If/Then" manual mapping.
Fails completely on typos or unstructured input.
Takes weeks to author and deploy basic flows.

Semantic AI

Generation can still be wrong. Evnao keeps source retrieval, provider results, approval controls, and human handoff visible so automation is not treated as certainty.

Inspect the workflow in context.

The guided demo shows an illustrative customer request and labels the view clearly so it is not confused with live tenant data.

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