docs(products): transcript product overview

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 # Transcript Forensics · product overview
 ## Pitch
 Audio counterpart to Blocao video forensics. Recordings of meetings, phone calls, depositions are processed on-site by Whisper + pyannote. The console offers natural-language query ("what was said about contract Acme and who was most insistent") with speaker identification, topic detection, and waveform-anchored playback.
 Built on the **same platform** as Blocao: same router, same Cell hardware (with a microphone or audio ingest interface), same MQTT bus, same GitOps, same hub.
 ## What you get
 - **Transcript console** with chat-style query, waveform with speaker bands, transcript navigable by speaker, audio player with live caption.
 - **Speaker library**: voiceprints stored per-customer, automatically matched against new sessions.
 - **Topic detection**: NER + clustering surfaces what was discussed; per-speaker breakdown.
 - **Insistence ranking**: identifies who pushed hardest on each topic (intervention rate, repetition).
 - **Pin to case**: same case management as Blocao video.
 - **Cross-product correlation** (Year 2): correlate audio transcripts with video events at a site.
 ## Use cases
 1. **Meeting forensics for legal/compliance**: review of depositions, board meetings, contract negotiations.
 2. **Customer service quality**: search support call recordings for problematic patterns.
 3. **Mediation and arbitration**: who said what, when, with audio proof.
 4. **Insurance claim review**: verify what was promised in pre-purchase calls.
 5. **Internal investigations**: HR or compliance review of recorded conversations.
 ## Why same platform as Blocao
 The transcriptor and Blocao share enough infrastructure that running them on separate stacks would be wasteful:
 - Same router, same Cell, same MQTT, same GitOps, same hub.
 - Same console patterns (chat, waveform/timeline, player, case management).
 - Same sovereignty model.
 - Same evidence chain (post-MVP).
 The only product-specific pieces are:
 - The Whisper + pyannote container in the Cell stack.
 - The speaker library schema in Qdrant.
 - The transcript-specific console panel.
 See [`shared-stack.md`](shared-stack.md) for the breakdown of shared vs distinct.
 ## Differentiators
 | Vs | Transcript Forensics differentiator |
 |---|---|
 | **Otter.ai / Sonix / Fireflies** | On-site processing + sovereignty + speaker library across sessions |
 | **Microsoft Azure Speech / AWS Transcribe** | No vendor lock-in + open-source models + same UX as Blocao |
 | **Open-source Whisper alone** | Fleet-managed + speaker identification + topic detection + UX |
 ## Status
 Mockup complete (`mockups/transcript-forensics.html`). Backlog at `backlog/transcript-sprint-backlog.md`. Many stories shared with Blocao backlog (see `backlog/shared-stories.md`).
 The transcript product launches **after** Blocao MVP is shipping (target: Year 2). Until then, design lives in this repo to ensure the platform is built with audio in mind from day one.