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A discovery-call transcript becomes 12 structured signals.

Upload a transcript from Otter, Fireflies, Whisper or Gemini. Annsa detects the speakers, the company, the date — then extracts the distinct signals and ties them to a customer record.

Discovery calls become structured feedback, in the same pipeline as everything else.

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— How it connects —

From raw transcript to customer record.

Four steps, the same pipeline as every other source.

01
Upload the file.

Paste, upload .txt or .md, or pull from Google Drive.

Source · upload
tandem-discovery.txtTXT
Pasted transcriptPaste
Q1 call notesDrive
02
Auto-detection runs.

Parsers cover Otter, Fireflies (SRT/VTT), Whisper (TXT/SRT/VTT/TSV/JSON), Grain, Google Meet Gemini and plain text. Title, date, customer name, company, email, plan, revenue band and transcript type are extracted from headers, speaker patterns, or the filename.

Detected
Simon HaleSpeaker
NorthwindCompany
Otter exportType
03
Multi-signal extraction.

One call mentions a co-edit conflict, slow onboarding and a missing notification — three distinct signals, not one blurry "call notes" entry.

1 call → 3 signals
AI rewrite collides on co-editBug
Onboarding too slowImprovement
@mention should notify on AI draftFeature
04
Customer record created.

Even a zero-signal context call still creates the customer record. Your CRM-of-voice stays complete.

Record
Northwind
Simon Hale · Enterprise · 3 signals
— What you get —

What the integration gives you.

Speakers and company auto-detected.

Drop the file in, no metadata entry. Otter, Gemini and "Meeting with X" patterns all recognised.

Sixteen-language support.

Non-English transcripts translate before classification, so a Japanese discovery call clusters with English customer feedback under one theme.

Content-hash deduplication.

Re-uploading the same transcript doesn't double-count. SHA-256 hash scoped per account.

— The proof —

Text minimum 50 characters, maximum 500 KB; title 1–500 chars. Each transcript becomes background-segmented into multiple feedback rows tagged source=‘transcript’.

— Questions —

Asked and answered.

Which transcript formats does annsa handle?

Otter, Fireflies (SRT/VTT), Whisper (TXT/SRT/VTT/TSV/JSON), Grain, Google Meet Gemini, plus generic .txt and .md.

How are speakers and company detected?

Pattern-matched from the transcript’s own headers and filename — "Meeting with [Company]", Otter-style speaker labels, Gemini exports, and so on. Manual override is available.

What if my transcript is in another language?

Annsa translates before classification. The cluster ends up under your existing English themes.

What if I upload the same transcript twice?

Deduped via SHA-256 content hash scoped to your account. The second upload doesn’t ingest.

Stop reading transcripts. Read priorities.

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Part of annsa’s autonomous product intelligence stack — see the full picture.