Conversational AI · Deep Sentiment Analyzer
AI that answers the phone — and understands every call
A conversational voice agent built into the phone system itself, and analytics that turn every recorded call into something you can search, score, and act on. All of it running on our infrastructure — your calls never train anyone else’s model.
Live demo
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Conversational AI
A voice agent that answers, holds a real conversation, and gets things done — not an IVR tree with a friendlier voice. It is a first-class part of the phone system, not a cloud API bolted onto the side.
Dedicated low-latency media server
The agent’s voice runs on a media server co-located with the phone platform, not a round-trip to a distant API. Responses come back in milliseconds, so the conversation has natural turn-taking and barge-in — callers can interrupt, and it stops and listens, like a person would.
Native SIP support
The agent is a real SIP endpoint on your PBX — it answers DIDs, sits in queues, and warm-transfers to a human on your existing trunks. No third-party bridge in the middle to add latency, cost, or another thing that breaks.
Domain memory
The agent remembers — but memory is organized into domains, not dumped into one shared vector store. Shared domains hold knowledge every agent can use; private domains keep each customer’s history walled off. Rules decide what’s shared and what stays isolated, so the agent speaks with full context without ever leaking one client’s conversations into another’s. Not just a similarity search.
MCP tool access
Through the Model Context Protocol, the agent can actually do things mid-call — look up an order, check a shipment, book an appointment, query your systems — using the same standardized tool interface our engineers build against. It is an agent that acts, not just a script that talks.
AI Call Analytics
Every recorded call, turned into structured, searchable intelligence — automatically, in the languages your business actually speaks.
Transcription & translation
Accurate transcripts in English, Russian, Spanish, Uzbek and more — with non-English calls translated and summarized in English so nothing is lost across a multilingual team.
Diarization & speaker roles
Calls are split by speaker and labeled by role, so a transcript reads like a script — and per-agent scorecards roll up automatically by extension.
Sentiment & frustration index
Every call scored for sentiment and a 1–10 frustration index, so the conversations that went wrong surface on their own instead of hiding in the archive.
Custom performance framework
Score calls against a framework built for your business — the categories, sub-questions, and red-flags that matter to you — with coaching notes and critical-case flags on every call.
Voice & language profiling
Per-speaker delivery analysis — pace, stress, language proficiency — turned into concrete, private coaching notes for your team.
Search every conversation
Semantic search across your entire call history — find every call about a topic, or pull up a caller’s full history before you pick up. The same retrieval memory the conversational agent draws on.
Who’s who, resolved
The platform builds a directory from your calls — the companies, people, and agents in them, resolved across every conversation even when a name is misspelled, each with their numbers, their history, and the facts that matter.
Track a case across calls
Follow a subject — an order, a claim, a deal — across a whole series of calls, with a rolling summary and the open issues kept current as new calls come in.
Reports & analyst workspace
Non-English calls are shown side by side, original and English, and exported as a PDF or text report — all in a secure dashboard with roles, per-team access, and search across everything.
Memory, organized into domains
Most “AI memory” is one big vector store — dump everything in, search by similarity. Ours is different: memory lives in domains, with explicit rules for what’s shared and what’s walled off. That governance — not raw search — is what makes it trustworthy, and what sets us apart.
Public, shared domains
Knowledge every agent can draw on — what your company does, your services, who’s who — lives in shared domains. Teach your agents once, in one place, and it’s there on every call. Within a domain, recall is semantic: the agent finds what matters by meaning, not keywords.
Isolated, private domains
Each customer’s and each caller’s history lives in its own domain, walled off at the core — isolated by default, not by a setting someone might forget. One client’s conversations never surface in another’s. The rules are explicit: call history stays private to its domain, while directory facts like a caller’s name can be shared — so a returning caller is greeted by name without ever exposing what they discussed. Predictable, auditable, private by default.
Your data stays yours
Transcription, analysis, and the conversational agent all run on EnableTalk infrastructure — not shipped off to a third-party AI vendor. Memory is isolated by domain, so one tenant’s calls never surface in another’s. Your conversations never train anyone else’s model, and recordings live where your compliance policy says they should.