Customer Feedback Synthesis Agent
An agent gathers feedback from Zendesk tickets, app store reviews, and G2 reviews, finds recurring themes, and sends a cited digest to leadership.
The problem
Customer feedback lands in disconnected places: support tickets, app store reviews, review sites. Nobody has time to read all of it, so decisions lean on anecdotes instead of the full picture. Recurring problems stay invisible until they show up in churn.
How it runs on Neblex
On a schedule, a deterministic flow pulls new feedback through the Zendesk, App Store Connect, and G2 connectors and hands it to the agent. The agent reads the batch, groups feedback into recurring themes, and links each theme back to the specific tickets and reviews behind it, so no theme floats free of evidence.
The agent writes a digest and posts it to product and CS leadership over Slack or Microsoft Teams. Raw feedback and theme assignments can be stored in Data Tables or your own Postgres database with SQL, so trends stay queryable over time, and durable memory lets the agent relate the current cycle to earlier ones.
If you want an editorial gate, the digest can require human approval before it posts, with the reviewer seeing the full draft and its supporting citations. Every pull, classification, and post is logged to the hash-chained audit trail, and failed runs replay from the exact failed step.
Step by step
Scheduled collection
A schedule triggers the flow, which pulls new feedback from Zendesk, App Store Connect, and G2.
Agent finds themes
Feedback is grouped into recurring themes, each linked to its source tickets and reviews.
Store for trend analysis
Themes and assignments land in Data Tables or your own Postgres database via SQL.
Digest is drafted
The agent writes a leadership digest with citations to the underlying feedback.
Optional approval gate
A reviewer can approve or reject the digest before it posts.
Delivered to leadership
The digest posts to Slack or Teams on the schedule you set.
Platform capabilities used
- Scheduled flows with an agent step
- Zendesk, App Store Connect, and G2 connectors
- Data Tables and SQL for trend storage
- Slack and Teams delivery
- Human-in-the-loop approval on the digest
- Hash-chained audit trail
Common questions
How do we know a theme reflects real feedback?
Every theme links back to the specific tickets and reviews it came from, so anyone can inspect the evidence directly. The digest can also pass through human approval before it posts, and every step is logged to the tamper-evident audit trail.
Can we query the feedback data ourselves?
Yes. Raw feedback and theme assignments can be written to Data Tables or your own Postgres database, where standard SQL works, so analysts can slice trends without going through the agent.
How often does the digest run?
On whatever schedule you set, and poll-based change detection can also pick up new feedback between runs. Failed runs retry and replay from the exact failed step, so a connector outage does not lose a cycle.
Related use cases
Support Triage Agent
A triage agent reads each Zendesk ticket, judges urgency and sentiment, drafts a reply, and escalates anything it is unsure about to a human for review.
Customer SuccessUsage-Based Health Scoring
Roll product usage from Snowflake into a Gainsight health score on a schedule and alert the account team in Slack when an account trends down.
AgenticSemantic Knowledge Search
Semantic search across your connected docs, wikis, and tickets: ask in plain language and get ranked, cited results from your own pgvector index.
Want this running on your stack?
Neblex Integration Fabric is in beta: full platform, free while in beta. Bring this workflow and we will map it to your systems.