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How Agni Handles Post-Call Summaries and Sentiment Analysis

After every call, Agni auto-generates a structured summary, tags the call with a sentiment score, and delivers both via webhookso your CRM stays current without manual notes.

AE
Agni EngineeringRavan.ai
17 May 2025  ·  6 min read
How Agni Handles Post-Call Summaries and Sentiment Analysis

A voice AI that makes calls but doesn't systematically report on those calls is half a product. The call happenedbut what was said? What did the customer feel? What was the outcome? What should happen next?

Agni answers all of these questions automatically, for every single call, within seconds of call completion.

What a Post-Call Summary Contains

At the end of every Agni call, the system generates a structured post-call summary containing:

  • Call outcome classification: One of a configured set of outcomes (e.g., Payment Promised, Call Back Requested, Not Interested, Transferred to Agent, No Answer, Voicemail)
  • Key data points extracted: Any structured data captured during the callpayment date promised, callback time requested, objection raised, address correction given
  • Natural language summary: A 2–4 sentence human-readable summary of the call, generated by the LLM from the transcript
  • Full transcript: Timestamped, speaker-separated text of the full conversation
  • Recording link: Secure URL to the call recording (stored on India-based servers, accessible for 2 years)
  • Sentiment score: A -1 to +1 scalar representing the overall customer sentiment across the call
  • Emotion tags: High-granularity tags for detected emotion segments (e.g., frustrated: 00:45–01:20, cooperative: 01:20–02:10)

Auto-tagging at scale: For a campaign of 10,000 calls, Agni generates 10,000 structured summaries automaticallyno human review required to get usable data into your CRM and analytics pipeline.

Sentiment Analysis: How It Works

Agni's sentiment analysis operates on two dimensions simultaneously:

Acoustic Sentiment (Emotion from Voice)

The audio signal itself carries emotional informationpitch variance, speaking rate, intensity, pauses. Agni's emotion model analyzes these acoustic features in real time throughout the call, producing a continuous emotion track. This track is then aggregated into the post-call sentiment score and emotion tags.

Acoustic sentiment catches things that words don't say: a customer who says "okay fine" in a frustrated tone is flagged differently from one who says it with genuine acceptance.

Semantic Sentiment (Emotion from Words)

The transcript is analyzed for semantic sentimentwhat was actually said. Complaint words, positive acknowledgment, threat language, and appreciation are all detected and weighted into the final sentiment score.

The combined acoustic + semantic score is more accurate than either alone, particularly for Indian languages where indirect expression is culturally more common than direct complaint.

Webhook Delivery: Real-Time CRM Updates

Post-call data is delivered via webhook to any configured endpoint within 30 seconds of call completion. The webhook payload is structured JSON containing all summary fieldsdesigned to be parsed and written directly to a CRM record without transformation.

Native integrations write directly to:

  • GoHighLevel: Contact notes, custom fields, opportunity stage updates
  • Salesforce: Activity log, custom object records, case updates
  • Zoho CRM: Call logs, notes, follow-up task creation
  • Freshdesk/Freshsales: Ticket updates, contact timeline
  • Custom webhook: Any endpointyour own database, your BI tool, your data warehouse

Analytics Dashboard

Beyond per-call summaries, Agni's analytics dashboard aggregates across your entire campaign and account history:

  • Sentiment distribution over timeare your customers getting more or less positive?
  • Outcome breakdown by agent, by campaign, by language cohort
  • Emotion heatmapswhich conversation segments generate frustration?
  • Transcript searchfind every call where a specific topic was mentioned
"We used to have a team of 4 people manually reviewing call recordings and writing notes. Agni's post-call summaries replaced that entirelyand the data quality is better because it's consistent across 100% of calls, not a 5% sample."Operations Director, NBFC (Pune)

Compliance Logging

Post-call summaries and recordings double as compliance artifacts. Every call's consent capture timestamp, disclosure text, and call recording are stored in a tamper-evident format for 2 yearssatisfying both RBI recording retention requirements and DPDP audit trail obligations.

Ready to get started?

Post-call summaries and sentiment analysis are included on all Agni plans. Access your analytics dashboard at app.ravan.ai. Webhook documentation at docs.ravan.ai.

Frequently asked questions

What is a post-call summary in voice AI?
A post-call summary is a structured, auto-generated recap of what happened on a call, including the caller's intent, key points discussed, outcome, and next actions. Agni produces this summary automatically after every call and delivers it via webhook, so your team gets consistent notes without any manual write-up.
How does Agni's sentiment analysis work?
Agni analyses the caller's tone, word choice, and conversational cues to assign each call a sentiment score, flagging whether the customer ended positive, neutral, or negative. This lets teams instantly triage unhappy callers for follow-up and track sentiment trends across a campaign without listening to every recording.
How are call summaries and sentiment delivered into my systems?
Agni pushes both the structured summary and the sentiment score via webhook the moment a call ends, and writes them back to your CRM automatically. With native GoHighLevel integration and a REST API, your contact records stay current in real time with no manual note-taking.
Why are automated post-call summaries valuable for high-volume Indian call operations?
When you run thousands of calls a day, manual note-taking is impossible and inconsistent. Automated summaries give every call a uniform, searchable record and sentiment tag, so managers can spot recovery risks, coaching needs, and dissatisfied customers across the whole campaign instead of sampling a handful of calls.
Can sentiment scores trigger automatic follow-up actions?
Yes. Because Agni delivers the sentiment score via webhook in real time, you can wire it to trigger actions such as routing negative-sentiment calls to a human agent, tagging the contact in your CRM, or scheduling a priority callback. This turns raw sentiment data into an automated escalation workflow.
Post-Call SummarySentiment AnalysisAnalyticsVoice AIProduct

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