How Atlas ERP transformed support transcripts into roadmap decisions
Atlas ERP ingests millions of customer interactions per quarter. With Bravin AI, their product leads receive curated insight packs highlighting failing modules and revenue opportunities.
Interactions analysed per week
1.8M
Across email, voice transcriptions, intercom, and partner portals
Insight digest latency
6h
From customer spike to executive dashboard notification
Churn reduction
-11%
Identified modules causing friction and released fixes within 14 days
What hurt before Bravin
Support escalations lived in separate tools, so leadership never saw cross-channel patterns early enough.
Manual tagging was inconsistent across regions, making global trend comparison impossible.
Developers relied on anecdotal evidence when prioritising bug fixes and feature enhancements.
How the rollout unfolds
Unified transcription stack
Voice calls, chats, and emails are standardised with entity recognition for modules, versions, and sentiment cues.
Executive weekly digest
AI summarises spikes, top complaints, and correlated revenue impact with recommended experiments.
- Dynamic filters by region, tier, or account manager
- One-click Jira issue creation with transcript evidence
Voice of customer council
Ops, product, and CX leaders meet bi-weekly with data-backed insights to greenlight roadmap changes.
What changed after launch
With patterns surfaced instantly, Atlas ERP fixed a billing reconciliation bug that previously caused two enterprise churns per quarter.
Critical bug resolution
-62% time
Now addressed within 36 hours thanks to automatic severity tagging
Upsell opportunities
+14%
AI flags accounts asking about advanced modules during support chat
NPS change
+9
Targeted fixes improved satisfaction for enterprise tier
Assets included
- Looker studio dashboard with role-based views
- Taxonomy for tagging features, sentiments, and intents
- Automation to auto-create Confluence insight briefs
Unlock hidden intent in your transcripts
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