Every call, meeting, and support interaction you've recorded is sitting as raw media — impossible to analyze, search, or extract signal from. LoreVault™ Media Transcription Service converts audio and video into structured, speaker-attributed conversational data that feeds directly into the broader LoreVault™ signal framework.
Most organizations record every customer interaction — then do nothing with them. Recordings sit in storage as binary files. They can't be searched. They can't be analyzed at scale. They can't be connected to ticket data, escalation patterns, or knowledge gaps. They're dark data.
Every output artifact is structured for both human review and machine ingestion. Speakers are disambiguated, timestamps are precise, and roles are inferred without manual tagging.
The entire pipeline runs in your environment — no recordings leave your infrastructure.
Audio and video files are ingested from your local storage, cloud bucket, or CX platform export. Supports common formats including MP3, MP4, WAV, M4A.
Speaker separation runs locally using on-device models. Each unique voice gets a persistent SPEAKER_ID. No cloud API calls. No audio transmitted externally.
Speech-to-text is performed locally using optimized local models. Each speaker segment is transcribed and timestamped, then merged into a unified output.
Role inference, optional participant mapping, and confidence scoring are applied. Output exports as structured JSON or text artifact — ready for LoreVault™ ingestion.
The service is designed to run where your data lives — on-premise in your own infrastructure, inside a customer environment under your management, or in a private cloud deployment on GCP or AWS. It uses local models only. No recordings, transcripts, or output data are transmitted to external APIs.
The transcription service handles any recorded audio or video interaction. Here are the most common deployments.
Inbound and outbound call recordings converted to structured agent/customer transcripts. Feed directly into LoreVault™ for escalation pattern analysis, knowledge gap detection, and compliance monitoring.
Recorded 1:1s, team meetings, and coaching calls processed into searchable transcripts with speaker attribution. Useful for QA workflows, training development, and knowledge base population.
Product demos, training screen recordings, and video walkthroughs converted to structured transcripts. Surface what was covered, who said what, and what questions arose — searchable and analyzable.
Existing libraries of recorded interactions that have never been processed. Batch transcription turns months or years of archived recordings into a searchable, analyzable interaction corpus.
Regulated interactions where conversation content must be reviewable. Structured transcripts with timestamps and speaker attribution provide auditable records that raw recordings cannot.
User interviews, customer research sessions, and usability recordings converted to structured transcripts. Extract themes, surface patterns, and build analyzable datasets from qualitative research.
The transcription service exists because LoreVault™ needs structured conversational data to do its job. Raw recordings can't be ingested into the signal framework. Transcripts can.
Once transcribed, every recording becomes a first-class LoreVault™ data source — indexed by the same domain lenses, queryable through the same interface, contributing to the same signal outputs as your case notes, tickets, and knowledge articles.
We scope engagements based on recording volume, environment, and downstream use within LoreVault™. Start with a 30-minute conversation — no pitch, no pressure.
Scoped per engagement · Runs in your environment · No external API calls