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LEO Soul by Kadropic Labs
Give Your AI Agent a Soul - A Way For Proper Judgement
LEO Soul is a metacognitive reliability layer for LLM agents, the grown up alternative to prompt only guardrails, it measures its own uncertainty, teaches itself in the background with online learning algorithm, follows its own genuine curiosity to close knowledge gaps, resists being talked out of the right answer, cuts hallucinations, and decides when to answer, ask, confirm, or refuse, a self learning agent brain runs fully on math, works with any model By Kadropic Labs.
Here's how this started, and it came from a bigger vision that isn't realistic at this moment:
I was building an agent for my own use case, and it kept doing the same thing: sounding 100% sure when it was flatly wrong, then folding the instant I pushed back, even when I was the one who was wrong. I got tired of patching this with longer prompts that just said be careful, so I started building a small layer to sit between my agent and the model and actually measure its uncertainty instead of guessing.
Somewhere in there I realized I wasn't solving my problem anymore — I was solving THE PROBLEM very agent in production has this same blind spot, it can't tell I'm sure from Im guessing, so it says both in the same confident voice.
I honestly wasn't sure this would generalize beyond my own use case. But it did, and that's LEO Soul now:
Knows when it's guessing , real math (semantic entropy, Bayesian calibration), not vibes or more prompts that drains tokens
Won't cave under pressure, re-derives from facts instead of folding
Decides + shows its work, answer/ask/confirm/refuse, with a full trace
Stateless, we store zero customer data, ever and it learns in the background in real neural network.
Free plan, no credit card. I'll be in the comments all day, ask me anything, including the stuff that broke while I was building this. 🙏
We Want to offer something different and exciting, User #333 & #444 who sign up will get Pro Plan for 3 Months for free + will get priority support and early access to beta features we're releasing soon :) + a surprise gift
Shout-out to my co-founder Mahantesh Hiremath for supporting me in every detail 🚀
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About LEO Soul by Kadropic Labs on Product Hunt
“Give Your AI Agent a Soul - A Way For Proper Judgement”
LEO Soul by Kadropic Labs was submitted on Product Hunt and earned 9 upvotes and 1 comments, placing #41 on the daily leaderboard. LEO Soul is a metacognitive reliability layer for LLM agents, the grown up alternative to prompt only guardrails, it measures its own uncertainty, teaches itself in the background with online learning algorithm, follows its own genuine curiosity to close knowledge gaps, resists being talked out of the right answer, cuts hallucinations, and decides when to answer, ask, confirm, or refuse, a self learning agent brain runs fully on math, works with any model By Kadropic Labs.
LEO Soul by Kadropic Labs was featured in SaaS (43.6k followers), Developer Tools (517.5k followers) and Artificial Intelligence (475.9k followers) on Product Hunt. Together, these topics include over 245.2k products, making this a competitive space to launch in.
Who hunted LEO Soul by Kadropic Labs ?
LEO Soul by Kadropic Labs was hunted by Bader Jamal. 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.
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Bader Jamal
Hey Product Hunt 👋
I'm the maker of LEO Soul by Kadropic Labs
Here's how this started, and it came from a bigger vision that isn't realistic at this moment:
I was building an agent for my own use case, and it kept doing the same thing: sounding 100% sure when it was flatly wrong, then folding the instant I pushed back, even when I was the one who was wrong. I got tired of patching this with longer prompts that just said be careful, so I started building a small layer to sit between my agent and the model and actually measure its uncertainty instead of guessing.
Somewhere in there I realized I wasn't solving my problem anymore — I was solving THE PROBLEM very agent in production has this same blind spot, it can't tell I'm sure from Im guessing, so it says both in the same confident voice.
I honestly wasn't sure this would generalize beyond my own use case. But it did, and that's LEO Soul now:
Knows when it's guessing , real math (semantic entropy, Bayesian calibration), not vibes or more prompts that drains tokens
Won't cave under pressure, re-derives from facts instead of folding
Decides + shows its work, answer/ask/confirm/refuse, with a full trace
Stateless, we store zero customer data, ever and it learns in the background in real neural network.
Free plan, no credit card. I'll be in the comments all day, ask me anything, including the stuff that broke while I was building this. 🙏
We Want to offer something different and exciting, User #333 & #444 who sign up will get Pro Plan for 3 Months for free + will get priority support and early access to beta features we're releasing soon :) + a surprise gift
Shout-out to my co-founder Mahantesh Hiremath for supporting me in every detail 🚀