Why full transcription wasn't the answer
Early on, we tried using full meeting transcriptions to power call summaries. It worked, technically. But reps hated reading walls of text. Managers ignored it. And it slowed our app to a crawl — both in processing and cost.
So we asked: what’s the minimum data required to extract actionable insight from a sales call?
Turns out, it’s not every word. It’s every signal.
Our new approach: capture signals, not scripts
Instead of transcribing the full call, we built a pipeline that:
Streams audio in real-time
Runs lightweight ASR (automatic speech recognition) tuned for intent, not syntax
Classifies phrases into semantic tags like
Next Step,Objection,Urgency, orBlockedSnaps timestamped highlights to the deal
Generates a bullet summary — not a script
The result? A clean recap under 5 seconds after the call ends — with all the right moments, and none of the noise.
Why it works better
Speed: Most summaries process in under 3 seconds
Privacy: No full transcript = less risk, easier compliance
Storage: We store just the insight layer — not the raw text or audio
Focus: Reps don’t get distracted by fluff. They see the action.
Bonus: It made UI better too
Because we only surface tagged moments (not transcripts), the UI is cleaner. Reps can skim the summary, hover over highlights, and jump into context when needed — without digging through a 45-minute call log.
And if they do need more, we retain the audio markers — so playback is still possible.
Final Thought
Sometimes, building fast software means letting go of “complete” and aiming for “correct + useful.” Sales teams don’t need a record of every word — they need clarity, momentum, and zero distractions.
