Source recording to reviewed transcript workspace

Reduce the time from raw recording to a reviewed, attributable transcript while keeping the recording and its text inside the owner's workspace. For law firms, journalists and research teams that turn recorded interviews, hearings and meetings into reviewed written records, convert owned audio and video files, speaker labels, language settings and editorial constraints into a reviewer-approved transcript with speaker attribution, summary and subtitle exports. The benefit is a testable hypothesis, measured through reviewed transcript minutes per editorial hour and corrections after review approval; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect owned audio and video files, speaker labels, language settings and editorial constraints, then follow this sequence: 1. Import audio and video files in common formats. 2. Transcribe speech into written text in many languages. 3. Label and rename speakers throughout the transcript. Resolve uncertain passages with qualified reviewers, approve the reviewer-approved transcript with speaker attribution, and measure reviewed transcript minutes per editorial hour and corrections after review approval against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved recording set and language list; final legal, editorial and quotation checks remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve speaker attribution, quotation accuracy, confidentiality and usage permissions. Named reviewers approve substantive changes and publication or filing scope. One approved recording set and language list; final legal, editorial and quotation checks remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One approved recording set and language list; final legal, editorial and quotation checks remain human. Implement one approved input format, a bounded representative case set and the first two task modules: import audio and video files in common formats; transcribe speech into written text in many languages. Support the third module with operator review: label and rename speakers throughout the transcript. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Owner-authorized recordings, cloud storage and platform links, and approved delivery destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Recording intake and settings, Editable transcript with audio sync, Review and delivery. Use a thumbnail list for recordings, a large central transcript canvas with a synced audio player, and a right-hand panel for speakers, language, glossary and comments. Let users compare transcript versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant passage and timestamp. Make the task-specific outcome reviewer-approved transcript with speaker attribution visible beside its evidence, review state and value baseline.