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ReguLattice AI Governance Platform
AI Governance Platform for AI Systems & Agents
ReguLattice is an AI-native governance platform that helps organizations discover, assess, govern, monitor, and improve AI systems and AI agents. It finds shadow AI, keeps people in charge of high-risk AI decisions, and maintains live, audit-ready evidence mapped to ISO/IEC 42001, the NIST AI RMF and the EU AI Act.
Hi everyone, I’m Moazzam, the maker of ReguLattice, from Karachi.
Companies are starting to let AI agents answer customers, change records and move money. I kept seeing the same gap: most AI governance is documents and dashboards that describe risk after the fact, and nothing stops a bad action while it’s happening.
So we built a gateway that sits in front of the AI. Every prompt, agent tool call and AI payment gets an answer: ALLOW, SIGN_OFF (a named person approves) or BLOCK. The answer comes from fixed rules, not another model, and if the gateway is down, the action doesn’t run. Every decision goes into a signed record that an auditor can check offline, without trusting us. It can also find AI tools your team uses without approval, and it can run entirely on your own servers with local models.
In our own red-team test, 215 attacks on the payments gateway were all blocked or held, and all 40 genuine payments went through. That is our own test, not an independent audit, and we have no revenue yet.
The sandbox asks for a name and email before it opens, so we can follow up with people who try it.
Who it’s for: teams in banks, fintechs and other regulated companies that want to use AI agents but must show a regulator that they’re in control.
I’d really like your feedback on two things: which attack should we try next, and what would you need to see before trusting a tool like this in front of your AI agents?
About ReguLattice AI Governance Platform on Product Hunt
“AI Governance Platform for AI Systems & Agents”
ReguLattice AI Governance Platform was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #159 on the daily leaderboard. ReguLattice is an AI-native governance platform that helps organizations discover, assess, govern, monitor, and improve AI systems and AI agents. It finds shadow AI, keeps people in charge of high-risk AI decisions, and maintains live, audit-ready evidence mapped to ISO/IEC 42001, the NIST AI RMF and the EU AI Act.
On the analytics side, ReguLattice AI Governance Platform competes within Developer Tools, Artificial Intelligence and Tech — topics that collectively have 1.6M followers on Product Hunt. The dashboard above tracks how ReguLattice AI Governance Platform performed against the three products that launched closest to it on the same day.
Who hunted ReguLattice AI Governance Platform?
ReguLattice AI Governance Platform was hunted by Moazzam Waheed. 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 ReguLattice AI Governance Platform including community comment highlights and product details, visit the product overview.
Moazzam Waheed
Hi everyone, I’m Moazzam, the maker of ReguLattice, from Karachi.
Companies are starting to let AI agents answer customers, change records and move money. I kept seeing the same gap: most AI governance is documents and dashboards that describe risk after the fact, and nothing stops a bad action while it’s happening.
So we built a gateway that sits in front of the AI. Every prompt, agent tool call and AI payment gets an answer: ALLOW, SIGN_OFF (a named person approves) or BLOCK. The answer comes from fixed rules, not another model, and if the gateway is down, the action doesn’t run. Every decision goes into a signed record that an auditor can check offline, without trusting us. It can also find AI tools your team uses without approval, and it can run entirely on your own servers with local models.
In our own red-team test, 215 attacks on the payments gateway were all blocked or held, and all 40 genuine payments went through. That is our own test, not an independent audit, and we have no revenue yet.
The sandbox asks for a name and email before it opens, so we can follow up with people who try it.
Who it’s for: teams in banks, fintechs and other regulated companies that want to use AI agents but must show a regulator that they’re in control.
I’d really like your feedback on two things: which attack should we try next, and what would you need to see before trusting a tool like this in front of your AI agents?