You know the drill. A customer writes in to say a button is broken. Someone on support asks for a screenshot, pastes it into a ticket, tags an engineer, and three days later the fix maybe ships. Nobody tells the customer. The whole trip from complaint to fix is a relay race with dropped batons at every handoff.
Gleap wants to run that relay for you with a set of AI agents that talk to each other. Support, product, and engineering all sit in one loop, and the pitch is bold: a bug a user reports can travel all the way to a merged code change with barely a human in the chain.
Quick facts
Pricing (as of 01 Jul 2026): paid, with a 14-day free trial. Plans run from Starter at $49/mo to Team at $149/mo, Pro at $299/mo, and Enterprise from $999/mo. AI usage is billed by actual tokens on top, roughly $0.04 per message on average. Web and mobile, with an SDK you drop into your app. Not open source. SOC 2 Type II audited and GDPR compliant, built in the EU.
What it actually is
Gleap is a customer support and product platform, but the interesting part is the crew of AI agents running it, all named Kai. Think of them as specialists rather than one do-everything bot.
Kai is the front-line support agent. It answers routine questions across chat, email, and other channels, in multiple languages, and Gleap says it clears about 80% of tier-1 tickets before a human ever opens them.
Kai Resolve is the investigator. When a question is too gnarly to auto-answer, it digs into the details, checks past tickets and connected data, and decides where the issue should go next.
Kai Code is the one that raises eyebrows. It takes a confirmed bug or an approved spec, works through a plan mode and a build mode, and opens an actual pull request (a proposed code change a developer can review and merge) in GitHub, GitLab, or Bitbucket.
Kai PM plays product manager. It groups similar feature requests, ranks them on a public roadmap, writes the spec, and pings the people who asked once the thing ships.
There is also a no-code builder, Kai Custom Agents, for wiring up your own agent against a thousand-odd other tools.
The real problem it fixes
Here is the moment Gleap is built for. A user on your mobile app taps a broken checkout button and reports it. Normally that report is a screenshot and a shrug. With Gleap, Kai Resolve grabs the technical evidence automatically: console logs, a session replay, the screenshot, the works. It sorts and routes the issue, spots that it's part of a recurring pattern, and if the bug is confirmed it hands the whole package to Kai Code, which drafts the fix as a pull request. When the fix ships, the person who reported it gets a notification. The loop closes on its own.
That last bit matters more than it sounds. The customer who bothered to tell you something was broken actually hears back. Most support stacks never manage that.
Where it's useful
A solo founder running a side project on the Starter plan points Kai at their help center and lets it answer the repetitive "how do I reset my password" messages at 2am, so they can sleep instead of babysitting a chat widget.
A support lead at a 15-person startup who is drowning in Intercom tickets lets Kai handle the easy half and routes only the real head-scratchers to her three human agents, which means the queue stops growing by lunchtime.
A product manager who used to keep feature requests in a messy spreadsheet lets Kai PM cluster the incoming asks, weight them, and publish a roadmap customers can actually see and vote on, so she stops guessing what to build next.
An engineering team at a fast-moving SaaS company lets Kai Code take the small, well-defined bug fixes off their plate as ready-to-review pull requests, so senior devs spend their week on the hard architecture work instead of one-line CSS fixes.
Why it stands out
Most support tools stop at the ticket. They log the complaint, maybe route it, and that's the end of their job. Gleap's whole reason for existing is to not stop there. The bug doesn't just get filed, it gets fixed and shipped, and the code change is the finish line rather than a well-worded reply.
The pricing model is worth a note too. Instead of charging a flat fee every time the AI resolves a ticket, Gleap bills by the tokens the AI actually burns, which it pegs at around four cents a message. If your volume is spiky, paying for work done rather than a success fee per resolution can land very differently on the invoice. Whether that's cheaper for you depends entirely on your ticket mix, so run your own numbers before you switch.
And if you already live in tools like Claude Code, Codex, or OpenCode, Kai Code can use your local setup rather than forcing you into its cloud. That's a rare bit of flexibility for a platform this opinionated.
How to try it
Start the 14-day free trial, drop the SDK into your app, and point Kai at your help center articles and your codebase. Gleap says most teams are live in under a day, and there are migration helpers if you're moving off Intercom, Zendesk, Canny, or Instabug. From there you can watch Kai field real conversations and decide how much rope to give the coding agent before it opens anything on its own.
One honest caveat: letting an AI open pull requests against your codebase is the kind of thing you'll want to supervise closely at first. "Self-driving" is a great tagline, but you're still the one merging the code. Start it on low-stakes bugs and build trust from there.
Takeaway
Gleap is betting that support, product, and engineering shouldn't be three separate tools with three separate silos. If the agents deliver even half of what the homepage promises, the payoff is real: fewer dropped tickets, a roadmap that reflects what users actually want, and small fixes that ship while your team focuses on the big stuff. The trial is free for two weeks, so the cost of finding out is mostly your time.