AI + human-in-the-loop operations
AI transcription and quality-control platform
A role-based transcription operation supporting AI-only, human-only, and AI-assisted delivery, from audio ingestion to a validated, formatted Word document.
Platform foundation
The challenge
Transcription is not a single AI request. Audio must be assigned, transcribed, corrected, formatted, proofread, validated, and exported while preserving speakers, timestamps, permissions, and an audit-friendly workflow.
The solution
We built one platform where automated speech engines and trained people work in the same production pipeline. Every unit has a clear status, responsible role, editing environment, quality gate, and delivery format.
End-to-end workflow
How the product moves work forward
- 01
Audio intake
Upload audio, create work units, capture metadata, and select the required transcription service.
- 02
Engine or human assignment
Send the unit to AWS Transcribe, NeMo ASR, another supported AI engine, or directly to a human transcriber.
- 03
Transcript enhancement
A transcriber edits the draft while listening to synchronized audio using custom keyboard playback controls.
- 04
Proofreading
A proofreader validates language, formatting, speaker labels, and transcript completeness before approval.
- 05
Delivery
Export to Word with or without bold, underline, speaker formatting, and other document styling.
Detailed capability map
What was designed into the platform
Roles and permissions
The right workspace for every participant
Permissions support the real operating model instead of giving every user the same controls.
Administrator
Manages users, work units, assignments, permissions, engines, and delivery status.
Transcriber
Creates a human transcript or enhances an AI-generated draft using the custom editor.
Proofreader
Reviews completed units, corrects issues, and validates the transcript for final delivery.
Viewer
Can securely review a shared transcript without changing its content.
Operational value
- Combines multiple transcription services in one operational workflow
- Keeps human quality control where AI confidence is not enough
- Reduces switching between audio players, text editors, and assignment tools
- Creates a repeatable path from raw audio to approved delivery
Growth opportunities
- AI confidence highlighting
- Terminology libraries by client
- Quality scoring by unit and transcriber
- Automatic speaker diarization review
Build on this experience
Have a workflow that needs its own product?
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