Cresta vs Speechmatics

Conversational research tool: poses natural-language questions over customer interaction data and returns evidence-grounded charts, comparisons and written answers.

Automated 24/7 phone-answering system for small businesses that captures leads, books/reschedules appointments, answers questions and routes calls.

A supervision surface for a contact centre running both people and AI agents, giving real-time oversight and guidance across the two.

Identifies which customer conversations are automation candidates, assigns a readiness score by volume/complexity/resolution rate, and exports discovered flows into Cresta's AI Agent Builder.

Real-time AI that listens to live contact-center conversations and surfaces behavioral coaching, source-backed answers and after-call summaries directly inside an agent's existing tools.

Analyzes 100% of customer conversations across human and AI agents to surface behavioral drivers of CSAT, handle time and revenue, combining Cresta Insights, Quality Management and Coach.

The no-code AI workflow engine that powers every Cresta product ('Opera GenAI Intents, Opera Workflows, Opera Analyzer'), letting contact-center teams configure and continuously optimize AI without writing code.

Continuously listens during customer interactions and surfaces precise answers in real time, grounded in conversation and on-screen context (account status, order history), guiding agents through complex workflows.

Analyzes conversation data to generate realistic customer personas, ranked by traffic volume and traced to source conversations, for AI-agent testing, human-agent training and voice-of-customer simulation.

Lets contact-center agents practice against AI-simulated customers built from real conversations, for onboarding, continuous skill development and targeted coaching.

Cresta's autonomous contact-centre agent, handling customer conversations end to end rather than coaching a human through them.

Speechmatics' automatic speech recognition API transcribes audio into text in 55+ languages in either real-time streaming or batch mode, with speaker diarization, custom dictionary, translation and summarization options.

Generates a short summary of an audio file in the same API call that transcribes it, as paragraphs or bullets. It is a Speech Intelligence feature enabled by adding a config block to a batch Speech to Text job, not a product bought on its own.

Speechmatics' text-to-speech API generates streaming synthetic English speech from text with sub-150ms latency using four named voices (Sarah, Theo, Megan, Jack), aimed at real-time voice agent use.

Translates a transcript into other languages in the same API call that produces it, for files or live audio. It is a feature switched on inside a Speech to Text request rather than a separate product; the docs file it under Speech to Text and return the translations alongside the transcript.

Speechmatics' voice agent offering provides a real-time conversational speech API - including the Flow WebSocket endpoint that chains speech-to-text, an LLM, text-to-speech and function calling - plus a Python Voice SDK for turn detection and speaker management, and integrations with Vapi, LiveKit and Pipecat.

A locally-executing speech-to-text engine for Mac and Windows laptops that runs on about one CPU core plus the device's neural engine or GPU and roughly 800MB of memory, sending no audio over a network and claiming accuracy within 5% of the cloud API.