Turn thousands of noisy support tickets, reviews, and transcripts into prioritized product insights — in seconds.
Presented by Victor Mwira · October 2026
Customer voice lives across Zendesk, App Store reviews, Intercom transcripts, NPS surveys, and Discord threads. Insights get buried. Bugs ship. Roadmaps misalign.
The average SaaS company processes this volume — and only reads ~5%.
Manual triaging means urgent bugs surface long after users complain.
Ignored feedback = canceled subscriptions. PMs feel it in the retention curve.
FeedbackLoop AI runs a 3-stage pipeline on every piece of customer voice:
CSV upload, manual paste, or API connectors
LLM extracts sentiment, category, summary, priority
Kanban dashboard with prioritized insights
What used to take a team of analysts a full sprint now happens in real time, for pennies per insight.
Drop in your raw feedback. Get a triaged board.
Structured chains handle ingestion → analysis → formatting with built-in retries and fallbacks.
Every insight is type-checked. No malformed categories, no missing fields, no garbage out.
Right-sized model for sentiment + classification. ~$0.15 per 1,000 insights.
Interactive Kanban with filters, search, and CSV export. Zero frontend code to maintain.
50–500 employees, drowning in tickets, no internal ML team. They feel the pain but can't build the solution. We charge $299/mo — pays for itself if we catch one churn risk per quarter.
GPT-4o-mini matches human accuracy on sentiment + categorization at 1/100th the cost.
Post-2024, every PM interview asks: "How do you measure customer impact?" PMs need this.
AI agents create tickets. Communities generate transcripts. The noise is getting louder.
To ship the Zendesk + Jira integrations, close our first 25 design partners, and prove retention.
Victor Mwira · victor@feedbackloop.ai · github.com/mwiravictor05-tech/flashbool
Questions?