Platform · Recordings & analytics

Debug voice calls like you debug code.

Every Vocily AI call becomes a structured execution record — full transcript, recording, sentiment, tool results, custom analysis, cost and latency breakdowns. Plus a Sentry-style event timeline so you can see exactly what happened, when, and how long it took.

Problem · Solution

The problem today

Most call platforms hand you a folder of MP3 files and call it analytics. QA listens to a random 1% sample and hopes that's representative. When a call goes sideways, the customer asks 'why didn't the bot use the manual?' and your team spends an hour scrubbing audio. Provider errors get re-skinned as 'something went wrong, please try again.' Cost lives in a billing dashboard nobody opens. Vocily AI takes the opposite approach: every call is a debuggable execution record, every event is its own row, every provider error is shown verbatim — debug like a developer, not like a guesser.

How Vocily AI handles it

  • Chronological event timeline

    Every STT, LLM, TTS, KB, tool, and error event is its own row with duration. Click to expand. A Sentry trace, but for voice calls.

  • Honest provider errors

    When Sarvam times out or Cartesia returns a 5xx, you see the exact code, message, and operation context. No marketing-speak hiding what failed.

  • Cost breakdown per call

    '₹4.20 = ₹1.10 Sarvam STT + ₹1.80 OpenAI + ₹0.90 Cartesia + ₹0.40 VoBiz' — real per-provider, per-call. Lets you optimise provider mix on actual spend.

  • Latency breakdown

    STT, LLM, TTS first-byte, and end-to-end latency averaged per call. See where the milliseconds go.

  • KB hits inline in the transcript

    Click any agent turn to see which document chunks grounded it, with retrieval score. The #1 customer debug question is now self-service.

  • Tool call inspector

    Request and response JSON for every API tool the LLM invoked, with args, response, status, and duration. Catch silent integration failures fast.

What's in it

What you can do with an execution record.

Every call produces one record with these surfaces. The pre-call analysis page (where you'd shape the agent) and the post-call review page (where you'd debug or audit) both read from this one structured object.

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Audio & transcript

The raw signal — captured, transcribed, and aligned.

Recording
Audio file per execution. Stops at human handoff so post-transfer conversations stay private.
Transcript
Full turn-by-turn with speaker labels (customer / agent).
Realtime alignment
Word-level alignment events persisted from the live conversation.
Language detected
Per-turn language tag — useful for multilingual calls.

Post-call analysis

Your own questions, answered automatically.

Custom analysis lets you define the questions you want answered about every call — from outcome category to compliance checks — and Vocily AI runs them across the transcript.

Sentiment
Outcome category
Compliance checks
Custom rubrics

Execution exec_29x8b

Post-call analysis

Outcome

Renewal accepted

Sentiment · customer

Neutral

Sentiment · agent

Supportive

Objection

Premium amount

Compliance read

Disclosed

Next step

Email confirmation

Common questions

What teams ask before they switch.

Sentiment is a built-in score that ships on every execution — customer mood, agent tone, overall trend. Custom analysis is whatever you define: boolean outputs ('did they book?'), text outputs ('what objection did they raise?'), or numbers ('lead score 1–10'). The platform runs both on every call.