For support teams
Your help docs answer the easy tickets. The rest wait on engineering.
Help articles cover the questions someone thought to write down. The tickets that break your SLAs are the ones nobody did: odd behaviour, edge cases, possible bugs. ProdE answers them from the code, tells you whether it is a bug, and hands engineering a root cause instead of a ticket.
The hard tickets are the ones nobody documented.
The ticket is not in the docs
The help center covers how the product should work. This ticket is about what it actually did, for one customer, in one configuration.
It goes to the engineering queue
Nobody in support can see the code, so the ticket is escalated and waits behind whatever the engineer is building.
The SLA slips
Days later the answer comes back. Often it was never a bug, only how the product works. The customer waited anyway.
Answer from the code. Escalate only real bugs.
Answer the tickets your docs do not cover
Ask how the product behaves in plain English. ProdE answers from your code across every connected repo, and shows the files and lines it came from.
Triage before you escalate
Bug, expected behaviour or a configuration issue? Which service owns it? Your team knows before anything reaches engineering, so only real bugs do.
Root cause on the ticket
On a Jira bug, run a root-cause analysis and it is posted back as a comment. Sentry errors are traced across repos with a likely cause and a suggested fix for an engineer to review.
Help articles that keep up with the product
When the code changes, ProdE updates the internal and external docs built from it, and flags articles in Confluence or Notion that no longer match the code.
Ask where you already work
Ask in Slack, in a DM or a thread, or wire ProdE into your own support bot over its API.
No code access needed
Your team never needs access to the repos to get an answer from them.
“Why might a customer with a valid card on file still see an account-suspended error?”
Attentive AI runs ProdE behind its support flow.
Their product spans hundreds of repositories, 29 active in ProdE. This is what happens when a customer needs help.Support needs data
Attentive built its own Slack bot and gave it ProdE's knowledge of their codebase. The bot pulls the code references from ProdE, queries the database with guardrails, and answers in Slack.
An error is flagged
When Sentry flags a problem, ProdE traces it across their repos and posts the likely root cause to Slack, so nobody has to dig for it by hand.
A person reviews it
An engineer reviews the analysis in Slack and decides what changes. Nothing reaches the code without a person.
Leena AI
5x faster tracing production issues across services. Less escalation, and clients back online faster.Attentive AI
930 production errors analyzed automatically, each with a likely root causeAttentive AI
40% of ProdE's traffic at Attentive is automated: Sentry errors with a root cause, data questions in SlackSend this part to your head of engineering.
ProdE needs read-only access to the repos you choose. Nothing else.It only reads your code
ProdE cannot change, commit, merge or push anything.
It never trains on your code
Your code is never used to train any model.
It never touches your running systems
ProdE reads the code. It does not connect to your application or your production data.
ISO 27001 certified
It runs in ProdE's cloud or on your own servers.
Kept current
Answers stay current with your code on a scheduled sync, as often as daily.
Works with your coding agents
Claude Code, Cursor, Codex, Copilot and any MCP client connect to it.
See it on your own codebase.
Connect your repositories to ProdE. Your team and your coding agents get the same map of the system.