Every product has a loop. A customer hits a problem. Someone answers. Someone investigates. Someone decides whether it is worth fixing. Someone fixes it. Someone tells the customer.
Most companies run that loop through five tools and five inboxes, and most of it never closes. Bugs live in support forever. Feature requests die in a spreadsheet. Engineers get tickets with no evidence and customers get a reply that says “we have passed this on to the team.”
We built Gleap to close that loop. Today we are saying plainly what Gleap has become: your AI software team.
What that means
Gleap is the platform where an AI team and your team build software together. The AI team has four members, and each one has exactly one job.
- Kai answers customers. It reads your help center, your docs, your snippets and your connected sources, answers in the customer’s language, and cites what it used. What it cannot answer, it hands on.
- Kai Resolve investigates the hard tickets. It has the session replay, the console and network logs, and your code. It reproduces the problem where it can and returns a verdict with the evidence: a bug, a feature request, an answer, or a case for a person.
- Kai PM decides what to build next. It reads every feature request, scores it against your goals and your customers, merges duplicates, and runs intake on the rules you write.
- Kai Code writes the fix. It takes a confirmed bug or an approved request, plans the change, writes the code and opens a pull request. It runs in Gleap Cloud or on your machine with your own Claude Code or Codex login.
Then the human part, which is the part that matters: your team reviews the verdict, decides what gets built, and merges the pull request. Nothing reaches a customer or a repository without a person saying yes.
Why a team, not a bot
The industry has spent two years building better chatbots. A better chatbot still ends at the reply. The ticket is closed, the bug is still in production, and the customer will write again next week.
A software team does not work like that. When a real support engineer sees the same crash three times, they open the logs. When a real product manager sees the same request from ten accounts, they put it on the roadmap. When a real engineer gets a reproduced bug with a stack trace, they fix it that afternoon. The work moves forward because each person hands it to the next one with the context attached.
That is what we built. Kai hands the ticket to Kai Resolve with the whole conversation. Kai Resolve hands the confirmed bug to Kai Code with the evidence. Kai Code hands the pull request to your engineers. The customer hears back after the release, on the same ticket they opened. One loop, one workspace, one customer record.
Why humans stay in the loop
We do not believe in “fully autonomous” software teams, and we do not sell one. The agents are good at the parts that were never worth a human’s afternoon: reading a thousand articles to answer one question, replaying a session to find the failing request, ranking three hundred requests against a goal, writing the first version of a fix.
They are not the right ones to decide what your product should be or what goes into your codebase. So every verdict is reviewable, every score is editable, every pull request waits for a merge, and every message to a customer goes through a tool you can switch off. Your team decides. That is not a limitation we accepted; it is the design.
What changes for you
If you run support, Kai answers first and your inbox receives the rest with the whole conversation and a verdict, not a forwarded thread.
If you run product, the requests arrive scored, deduplicated and linked to the tickets behind them. You move a request to Planned when the score and the votes agree, and the people who voted hear when it ships.
If you write code, the bug arrives with the session, the log line and the commit. The fix arrives as a pull request. You review it the way you review a teammate’s work.
If you run the company, every ticket ends in shipped code or a deliberate decision not to ship, and you can see which.
Where we are going
Gleap already runs the inbox across seven channels, bug reports with session replay, feature requests and the public roadmap, the knowledge base, release notes and outreach. The agents work on top of all of it, and they will keep getting closer to the code and closer to the customer.
Our measure is simple. Not how many tickets an agent closed, but how many customer problems ended in a shipped change with a human who chose it.
If that is the kind of team you want behind your product, start a free trial or see how the agents work together.