Product memory

Your product remembers everything. Now you can ask it.

Every call, ticket, and idea becomes one memory of what customers actually need, classified in your own taxonomy. Question it in plain language, slice it by segment or account, and give your AI agents the same memory to build from. In a conversation, or a view built for the question.

ZentrikDiscovery workspace
Where are enterprise accounts feeling the most friction?
Read against your Enterprise segment and problem areas
Three insights, all from enterprise accounts. Open any of them:
Admin SSO recovery is opaque during callback failures
InsightEnterprise· Zendesk, Gong
SSO failures need guided recovery for portal users
InsightEnterprise· 3 accounts
SFTP loading breaks with vendor file format changes
InsightEnterprise· 2 accounts
Two of the three are SSO recovery. Fix onboarding reliability and you clear the loudest enterprise complaint at once.

Building stopped being the hard part.

Your team can ship a feature in the time it used to take to write the spec. What has not sped up is the decision underneath it: given everything customers are telling you, what is actually worth building next.

That decision is only as good as the evidence you can bring to it, and the evidence is usually one more search away, buried in a call from three weeks ago or a ticket nobody linked. So the meeting runs on memory and the strongest opinion, and the roadmap quietly absorbs the guess.

Zentrik keeps the evidence in one place and lets you question it directly, in the words your team already uses. The answer above came from a few hundred insights. Every line in it opens.

An answer you can defend.

A decision made in the chat has to survive the room. So the conversation and the Discovery views your team opens read from the same evidence, filtered the same way. When Zentrik says eighteen accounts, someone can open the eighteen.

Workspace chat
Banking evaluators need read-only briefs
Audit export timeouts hinder reviews
Delivery sync needs retry and audit states
=
Discovery table
Banking evaluators need read-only briefs
Audit export timeouts hinder reviews
Delivery sync needs retry and audit states

Same evidence, same filter, same rows. What you decide from is what your team sees, because it is the same query.

Ask it, or watch it.

Discovery is not a report you run once. New calls, tickets, and ideas land every week, and last month's read goes stale. Some questions you are still figuring out. Others you have already decided matter. Same evidence underneath, two ways to hold it.

Explore in a conversation

Follow the thread. Change the segment, widen the window, ask the follow-up. Right for the question you have not answered yet.

Keep it as a view

Pin the slice that matters and keep it on screen. It refreshes as new evidence lands, so the watch runs itself.

The same product context for the agents beside you.

The agents you point at your product, from Cursor to Claude Code, should not work from a brief someone typed once and left to rot. They read the same grounded graph your team does, so what they build traces back to real customers. It is the product context your AI builders have been missing.

CLASSIFIEDCUSTOMER SIGNAL, AS IT ARRIVESCallsTicketsIdeas & notesDocsYour product memoryYour evidence, classified in yourown taxonomy and kept in sync.segmentsthemespillarsone query · one answer · one source of truthYour teamin chat, or a pinned viewYour agentsCursor, Claude Code, the same ground

Questions people ask before they start.

Can I ask questions about my customer feedback?
Yes. Zentrik turns your calls, support tickets, and product ideas into evidence you can question in plain language, sliced by the segments, themes, and accounts you care about. Every answer is drawn from real insights you can open.
How is this different from prioritization or a roadmap?
This is where you interrogate the evidence. Prioritization and roadmap are where you rank and sequence what you have already decided to build. You ask first to figure out what matters, then carry the evidence into planning.
Do the chat answers match what my team sees in Discovery?
Yes. The chat and your Discovery views run the same query over the same evidence, so a count in the conversation is the same count on the screen. A decision made in chat holds up when your team opens the table.
Can my AI coding agents use the same product context?
Yes. The same grounded graph is open to agents over MCP, so Cursor, Claude Code, and any connected agent work from real product context instead of a brief someone typed once and left to rot.
What sources does Zentrik draw from?
Customer calls, support tickets, product ideas, and documents, classified into your own taxonomy and kept in sync as new evidence lands. You ask in your own words, not a query language.

The next time someone asks why this and not that, the answer is a question away.

A roadmap you can question in the open is a roadmap you can defend. Bring your evidence and try it against a decision you already made.

Every screen here is drawn from a real Zentrik workspace. Records, segments, and counts are actual discovery data.