The Friction
"Manual transcription is slow and expensive; valuable data in voice calls is often lost or unsearchable."
An AI engine that instantly transcribes audio and identifies speakers, making voice data accessible and analyzable.
Philosophy: Unlocking the value of voice.
Automated Transcription
Converts speech to text with high accuracy.
Speaker Identification
Distinguishes between different speakers in a conversation.
API Integration
Easily embeds into existing workflows.
Neural Path
Audio Input
AI Processing
Text/Speaker Output
Technology Stack
Impact
Delivers transcripts in seconds; makes audio data searchable and actionable.
Further reading
Transforming 10,000+ Weekly Sales Calls into Actionable Intelligence with LipiQ
A mid-market SaaS company deployed LipiQ to automatically transcribe, diarize, and analyze every sales and customer success call—eliminating manual note-taking and surfacing conversation insights that increased win rates by 22%.
The Untapped Data Asset: Why Enterprise Voice Data Is Sitting Unused
Sales calls, client meetings, support calls, board discussions — enterprises generate thousands of hours of voice data weekly. Almost none of it is analyzed. That's a significant missed opportunity.
Speaker Diarization: The Technology Behind Who Said What
A transcript that reads 'Speaker 1: ... Speaker 2: ...' is less useful than one that reads 'Client: ... Account Manager: ...' Accurate speaker attribution transforms meeting records from notes to intelligence.