Lunen.ai

The thing that stands out to me is keeping a clear record of what the AI actually did. Wanting the convenience without giving up the ability to answer for it later feels like the sensible way to approach all of this.

Finally a tool that keeps the consumer feel but actually shows you what happened under the hood. The approval flow for risky steps felt thoughtful, not bureaucratic.

One thing that would help my team a lot is a side-by-side replay viewer that shows what the agent did step by step with diffs, so I can review an overnight run in a few minutes instead of digging through logs. That kind of timeline with redo and undo per step would make the whole governance story actually usable day to day.

Having built self-hosted MCP agents, governance is always the bottleneck: defining unattended vs. human-in-the-loop actions and auditing the aftermath. You can ignore this solo, but it kills enterprise adoption.The "allow reads, approve writes" approach with unified audit logs targets this perfectly, though I'm curious if it survives a real security review.For anyone running agents in production: where do you draw the line for human intervention? That’s the boundary I find hardest to define.

The control surface matters as much as the agent. For team-run agents, I would want permissions, dry-run mode, approval points, and logs to be first-class, because the failure mode is not that the agent is slow; it is that it acts confidently in the wrong system.

Finally something that doesn't make me choose between a nice interface and actual visibility. Tried a small workflow and the audit trail was already there without me digging for it.

Clean interface that doesn't feel like another enterprise dashboard, and I was surprised the approval workflow didn't slow things down.

Finally tried it this morning and the approval log before risky steps actually feels useful, not just busywork. The fact that I can see exactly what the agent touched makes me way more comfortable letting it loose on real files.

I've had access to Lunen for a few weeks and have an agent that runs daily that is saving me hours of work per week, and will only continue to get better as I refine and have an agent that can build these agents for me.

Hey Product Hunt 👋, I'm Mike, from the Lunen founding team.

You've used ChatGPT and Claude for real work by now. You ask for something, it goes and does it. That's the pitch, and it's also the problem. It just does it. No record of what it touched, no point where it stops and lets you approve the risky part, nothing you'd feel good putting in front of your security team. Amazing to use, impossible to govern.

The enterprise tools that fix the governance side have the opposite problem. Locked down, fully audited, and nobody wants to open them. So every company I talk to is quietly picking one. Fast and ungoverned, or safe and unused.

My belief is you should never have to pick. Lunen is the AI you already know how to use, except you can see and control every move it makes.

It works because we refused to build it the normal way. Normally the people who want agents grab a tool IT never signed off on, and IT buys a governance layer nobody wants to touch. Two products, two teams, a gap in the middle where the AI project quietly dies. In Lunen it's one path. The same steps someone in accounting takes to describe an agent are the steps that scope its data, set its permissions, and log what it does.

What that gets you:

Describe the agent in plain language and the plan writes itself. Named tools, scoped data, a schedule. No builder to learn, no YAML. Allow the reads, approve the writes. Every tool is a policy decision. It runs on its own, or it waits for human-in-the-loop before it calls, like a 2FA checkpoint. Same rules for every agent and every one-off run.

Every action on the record. People and agents land in one audit log. Click any event and you see who did it, what got approved, which model ran, and what data it touched. Hand it straight to a reviewer. Agent have their own identity, so you can easily see and track what YOU did with an agent, what an agent did independently, and what an agent did on your approval.

Where this comes from:

We built Lunen inside REDspace, where we've spent 25+ years shipping enterprise platforms for some of the biggest media and tech companies out there. We watched a lot of good AI work die in security reviews. Got tired of it. Built this. So we first started by solving the problem for ourselves and now it's time to share it outwards.

We're in early access now, working hands-on with the teams we bring on. If your org is trying to get AI past its own security review, come get early access and I'll get you set up.

I'm in the comments all day. What's the riskiest thing you've let an AI do with no record of it?