AI-Native Feedback

Feedback that understands itself

Build forms with a prompt. Search responses by meaning. Turn a thousand comments into three action items. And let your AI agents file feedback while they work.

Try it freeAI agent docs
🪄

AI form builder

Describe the survey you need — "post-onboarding NPS with a follow-up comment" — and Pollenate drafts the questions, types, and options for you to edit.

📊

AI insights

Turn hundreds of raw comments into themes, sentiment breakdowns, and concrete recommendations with one click. Know what to fix next without reading everything.

🔍

Semantic search

Search feedback by meaning. A query for "checkout is confusing" finds "paying was hard" and "couldn't figure out billing" — no keyword overlap required.

🧩

MCP server

A built-in Model Context Protocol server lets Claude Desktop, Cursor, and any MCP client submit feedback, query stats, and browse inboxes directly.

🤖

Agent feedback ingestion

AI agents and chatbots report user satisfaction as it happens — attach agent name, session ID, and arbitrary context to every event via one POST.

🎙️

Voice feedback

Feedback pages support voice recordings alongside 17 other question types, so users can just say what they think — and you can analyze it later.

AI at every step of the loop

01

Create

Prompt the AI form builder to draft your survey — 18 question types including voice — then tweak and publish.

02

Collect

Widgets, feedback pages, the REST API, Zapier, and MCP-connected agents all feed the same inboxes.

03

Understand

Semantic search finds what users mean; AI insight reports surface themes, sentiment, and recommendations.

04

Act

Webhook automations, issue tracker links, and status workflows turn insight into shipped fixes.

Building with the API instead? See the Developer Feedback API →

Frequently Asked Questions

What does "AI-native" mean in Pollenate?
AI is built into each stage of the feedback loop: generating forms from a text prompt, semantic vector search over collected feedback, AI-generated insight reports with themes and sentiment, and an MCP server so AI agents can submit and query feedback programmatically.
How do AI agents submit feedback?
Two ways: a plain POST to /collect with an API key, or through the built-in MCP server at /mcp which exposes tools like submit_feedback and get_feedback_stats to Claude, Cursor, and other MCP clients.
How does semantic search work?
Feedback comments are converted to vector embeddings and stored in an isolated, per-organization index. Searches are embedded the same way and matched by cosine similarity, so results are ranked by meaning rather than exact keywords.
Which plans include the AI features?
Semantic search, the MCP server, agent ingestion via /collect, and the AI form builder are available to every organization — each plan includes a daily search allowance. AI insight reports are included on paid plans (Team and Enterprise).
Is my feedback data used to train AI models?
No. Your feedback is processed to serve your own features — search, insights, form generation — and is never used to train foundation models.

Stop reading feedback. Start understanding it.

Free to start — 5,000 events a month, no credit card.

Get started freeView pricing