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Technical Specifications

The Speekee Engine

Under the hood of our zero-latency autonomous call operators. How we translate voice into API events in under 400 milliseconds.

Step 01

Real-time Telephony

Using Twilio SIP media streaming, we feed live raw audio chunks into a dual-direction WebSocket gateway. Zero buffer lag, direct trunking support with any carrier.

Step 02

Cognitive AI Parser

Real-time transcripts from Deepgram are evaluated by low-latency LLMs. The parser detects intent, checks logic flows, and compiles dynamic response branches.

Step 03

Action Triggers

Invokes custom API endpoints, books into databases, reschedules CRMs, or gathers human handoff approvals — all inside the live call stream.

Key Technical Features

Built for production-grade voice deployments at scale.

v2.4 Engine

Interruptible Barge-In

Callers can cut off the voice assistant mid-sentence. The engine stops audio streaming instantly, captures the new statement, and updates conversational context.

CRM & API Lookup Filters

Before the conversation greeting begins, a fast parallel GET hits your CRM to fetch profile names, outstanding orders, loyalty flags, and appointment history.

Manual Handoff Approvals

High-risk operations (e.g., refunds) can be held in a pending confirmation state. The agent notifies operators via webhook while keeping the caller on the line.

Multi-Tenant Logging Streams

Each tenant logs actions, transcripts, LLM prompt templates, and REST execution payloads — providing developers with rich tracing and debugging tools.

Integrations

Works With Your Stack

OpenAI, LM Studio, Twilio, Deepgram, Bland AI, custom CRMs, Zapier webhooks, and any REST-compliant API.

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