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Lelu-ai
Stop manipulated AI agents before they act
AI agents now take real actions—refunds, emails, deploys. Existing tools secure WHO an agent is (OAuth/identity); none answer whether an authorized agent is being manipulated right now. Lelu is the behavioral layer that authorizes every tool call before it runs—catching prompt injection and low-confidence actions. Confidence comes from the model's logprobs, not a number the agent can fake. Four outcomes: allow, deny, human-review, or a safe alternative. Open source & self-hosted.
Hey Product Hunt! 👋 I'm Abenezer, the maker of Lelu-ai.
I build AI agents and train models, and the thing that kept nagging me was the asymmetry: everyone's racing to give agents more power — more tools, more autonomy — and almost no one is building the brakes. When an agent gets it wrong, it's not a typo. It's a refund issued, a record deleted, an email sent to the wrong person — instant and irreversible. And "the model was confident" is no defense.
So I built Lelu: a safety layer that authorizes every agent action before it runs. It catches prompt injection, gates on the model's real confidence, and routes uncertain calls to a human — returning allow, deny, human-review, or a safe alternative.
The one insight behind it: you can't trust an agent's self-reported confidence — a manipulated agent will happily claim it's 100% sure. So Lelu derives confidence from the model's token log-probabilities, something the agent can't fake.
It's fully open source (MIT) and self-hosted — your data never leaves your infra. Works with LangChain, CrewAI, MCP, and Amazon Bedrock out of the box.
I'd genuinely love your feedback — especially from folks running agents in production: how do you decide when an agent is "sure enough" to take an irreversible action? PRs and issues are very welcome too. 🙏
Repo: github.com/lelu-auth/lelu
About Lelu-ai on Product Hunt
“Stop manipulated AI agents before they act”
Lelu-ai was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #15 on the daily leaderboard. AI agents now take real actions—refunds, emails, deploys. Existing tools secure WHO an agent is (OAuth/identity); none answer whether an authorized agent is being manipulated right now. Lelu is the behavioral layer that authorizes every tool call before it runs—catching prompt injection and low-confidence actions. Confidence comes from the model's logprobs, not a number the agent can fake. Four outcomes: allow, deny, human-review, or a safe alternative. Open source & self-hosted.
On the analytics side, Lelu-ai competes within API, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Lelu-ai performed against the three products that launched closest to it on the same day.
Who hunted Lelu-ai?
Lelu-ai was hunted by Abenezer. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Lelu-ai including community comment highlights and product details, visit the product overview.
Abenezer