THE PLATFORM

A conversational AI engine built around context - not just a language model with a transcript bolted on.

View Full Platform Details

Architecture that takes context seriously

Most conversational AI APIs accept a message array and return a response. That's not dialogue management - it's stateless text completion. Equmenopolis maintains a typed session state that persists entities, tracks resolved intents, and carries coreference chains across the full conversation.

When your user says "fix that third issue we discussed," the platform knows what "that" refers to, which issue index "third" maps to, and that "we discussed" is a past-session reference. It doesn't hallucinate a plausible answer - it resolves it from the tracked state.

Explore Full Platform
Equmenopolis Platform Dashboard

CORE COMPONENTS

Intent Recognition

Intent Recognition

Structured intent mapping with entity slots. Handles multi-intent utterances and intent correction mid-dialog. 300+ pre-built intents.

Context Memory

Context Memory

Typed session state persists entities, intent history, and coreference chains. Lookups resolve correctly across a full 50-turn session.

Multi-turn Dialog

Dialog Manager

JSON state machine dialog flows. Slot filling, clarification handling, topic switching - all server-side without client-side logic.

API

REST API

Single POST endpoint. P95 latency under 80ms. SDKs for Python, Node.js, and Go. WebSocket for real-time applications.

Analytics

Dialog Analytics

Turn-level metrics on intent confidence, fallback rates, and context hit ratios. Identify exactly where conversations break.

Security

Enterprise Security

SOC 2 Type II certified. Data never used for training. Context objects encrypted at rest with AES-256. EU and US regions.

Read the full platform docs

Deep-dive into the API reference, dialog flows, and context state architecture.

Full Platform Details