Feedback brief ready!
Customer issue summarized for review
Zens AI
Answer website and in-product questions around the clock, identify customers, and capture recurring feedback. A conversion copilot for independent developers.

Welcome, Jane
Illustrative dataCustomizeRecent conversations
| Time | Visitor | Topic | Status |
|---|---|---|---|
| 10:42 | Acme | Team permissions | AI drafting |
| 10:31 | Northstar | Security review | Resolved |
| 10:18 | Kite | Workspace setup | Resolved |
| 09:56 | Orbit | Billing limits | Assigned |
Customer issue summarized for review
Slack, GitHub, Zapier + SDKs
AI-assisted workflows connect conversations, feedback, and product work.
from first message to team handoff
Catch identity, intent, risk, and the next team action inside every conversation.
Your agent
Find the three questions high-intent accounts asked most often in the last 7 days.
Product overview
In 33 seconds, follow the loop from repeated questions and customer context to prioritized product work for Codex, Linear, Slack, and GitHub.
The real bottleneck
Zens AI starts from the painful moments that block SaaS growth: repeated support work, delayed replies, buried feedback, and a loop engineering system without enough user evidence.
What Zens AI changes
Capture the question once, answer faster next time, cluster the feedback, and hand the evidence to product, engineering, Codex, Slack, Linear, or GitHub.
The same pricing, setup, login, and integration questions keep coming back, and teammates lose hours repeating answers that should already be captured.
Support time is spent on repetition instead of high-value users.
When the team is away from the computer, high-intent visitors wait too long, lose momentum, and leave before a paid conversion can happen.
Slow replies turn purchase intent into missed revenue.
Bugs, objections, and feature requests stay buried inside conversations instead of becoming clear product requirements with evidence and owner context.
Product teams miss the signals users already gave them.
Without a steady user feedback layer, teams cannot build a self-iterating loop engineering system across support, product, engineering, and agents.
Every iteration starts from opinion instead of customer evidence.
Agent actions
Zens AI turns in-product support into a searchable, clusterable, handoff-ready context layer, so teams and agents can start from real customer problems.
From conversation to implementation
Zens AI packages repeated feedback into a brief with affected routes, reproduction details, and acceptance criteria.
Zens action runner
Codex
Customer signal
5 conversations report the same signed-identity failure
Search conversations
5 matching reports
Assemble evidence
/auth and /docs/install
Define acceptance
3 checks included
Codex
Implementation brief ready
Supported services
From identity to conversation summaries, from product feedback to Codex tasks, Zens AI turns real in-product problems into workflows your team can move forward.
Signed user
Verify signed-in users and anonymous visitors
Account traits
Plan, role, lifecycle, and workspace context
Session timeline
Pages, events, and recent product behavior
Permission scope
Trim context by team role
AI inbox
Keep questions and account signals together
Live handoff
Attach summaries when handing off to a human
Reply drafts
Generate reviewable replies from trusted context
Help draft
Turn repeated questions into help content
SLA signals
Spot delay, escalation, and account risk
Bug themes
Cluster issues that block product use
Feature requests
Keep real requests with account evidence
Pricing objections
Find doubts before conversion
UX friction
Reveal page and flow blockers
Codex brief
Move into implementation with evidence
Multica context
Give team agents customer background
Slack handoff
Push key conversations into channels
Linear issue
Create tasks with acceptance criteria
GitHub issue
Carry fix scope and evidence into GitHub
Weekly report
Summarize the team report automatically
Event stream
Connect product events and page context
Page context
Know where users ask for help
Revenue traits
Use plan and account data safely
Segment exports
Sync to analytics and growth systems
Workspace search
Search themes and customers across conversations
Signed identity
Prevent forged account context
Role controls
Limit visible fields by team role
Audit log
Record who viewed or exported data
No training
Keep customer conversations out of model training
Core capabilities
It is not another inbox for support. It turns customer context into a safe working layer for agents, product teams, and the rest of your company.
Zens AI capability
verified
summarized
actionable
How it works
You do not need to rebuild team workflows. Identify the user, connect the conversation, then send the insight to the engineering and collaboration tools you already use.
Create a workspace, receive a site ID and signing secret, and decide which user fields are allowed in support context.
site: zens.ai
identity: signed
mode: review-firstAdd the SDK to your product, then sync user, account, plan, and current page after login.
<script src="https://zens.ai/sdk.js" />
Zens.identify(user, account)Send repeated questions, human handoffs, and product briefs into the tools your team already uses.
Codex brief -> Linear issue
Slack handoff -> Support leadFAQ
Zens AI is more than a chat window. It brings user identity, account state, current page, product events, and conversation history into one trusted context layer, so support replies, product feedback, and agent tasks all work from the same evidence.
Zens AI is built for SaaS teams that want support conversations to drive product improvements, especially founders, support leads, product managers, growth teams, and engineering teams adopting agent workflows.
Review-first is the default. AI can draft replies, summaries, and recommendations, while your team controls what can be automated and what must be approved by a human.
Yes. Zens AI can turn repeated feedback into Codex-ready briefs and send context to Slack, Linear, GitHub, Multica, or other team agents.
Customer conversations are not used for model training by default. Zens AI emphasizes signed identity, role controls, private fields, and data minimization so agents only receive the context needed for the task.
Use real customer context to drive replies, summaries, product improvements, and Codex tasks, turning every conversation into the next iteration.
Start free