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.
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.
RAG memory
The agent remembers. Before it answers, it retrieves prior conversations with the same caller and the relevant facts from your own knowledge base, so it speaks with context instead of starting from a blank slate every time. Repeat callers do not have to repeat themselves.
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.
Memory that connects every call
Most call tools treat every call as an island. Ours remembers — and connects the dots across your entire history.
Hybrid memory
Every call is remembered two ways at once: instant recall of a specific caller’s own history, and meaning-based search across your whole archive. Ask in plain language and get back every call that actually matters — not just the ones that happen to share a keyword. The conversational agent draws on the same memory live, mid-call.
Cross-call connectivity
The system recognizes the same speaker across different calls — and even different numbers — links related conversations into one connected thread, and surfaces the patterns that only show up across a series of calls: a recurring complaint, an escalating situation, a story that unfolds over weeks. Context a single-call view can never see.
Your data stays yours
Transcription, analysis, and the conversational agent all run on EnableTalk infrastructure — not shipped off to a third-party AI vendor. Your conversations never train anyone else’s model, and recordings live where your compliance policy says they should.