The San Francisco
Voice Company
Search for
# Find every call where the agent interrupted the caller
voice.query("calls where the agent interrupted the caller.")
→ 1,284 matches
→ clustered into 6 defect signaturesBuilt for teams running 10K+ calls/day.
- LiveKit
- Twilio
- Telnyx
- Pipecat
- Datadog
Beyond words
Most systems hear words.
We hear everything.
Meaning lives beneath the surface of speech.
What others hear
The surface
Words and transcripts
What we hear
The depth
Acoustic features
Keyword search
Finds “cancel subscription”
vsAcoustic features
Detects frustration
Transcription
Captures what was spoken
vsProsody capture
Captures how it was said
Analytics dashboards
Summarize after the fact
vsLive detection
Surfaces signals instantly
AI-native output
Made to be read by the LLMs already debugging your stack.
Structured for LLMs
Replay bundles, defect signatures, and corpus search results ship as structured, machine-readable output. Claude, Cursor, and Cline can reason over a voice failure without prompt gymnastics.
MCP server, voice-native
A drop-in MCP server exposes your corpus to your debugger. Better than Datadog's MCP for voice — the schema is built around turns, audio, and replays, not flat metrics.
Applicable for Datadog usersReplay → root cause in one loop
Paste a defect signature into your AI assistant. Get the failing turn, the model parameters, the audio link, and the next step — without leaving the chat.
