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AIBIM AI
Runtime security for AI apps and agents
AIBIM is free AI runtime security for LLM apps and agents. Monitor prompts, responses, tool calls, and agent behavior in real time. Apply policies to flag, redact, block, or route risky activity for human review. Keep every risk, decision, action, and owner connected in a traceable review record. Connect through documented SDK and supported Desktop Agent paths. Free access is currently available through a controlled beta.
I built AIBIM because teams are shipping LLM apps and AI agents faster than they can answer basic runtime security questions: What did the model receive? What did it return? Which tools did the agent call? Why was risky activity allowed or blocked?
AIBIM monitors prompts, responses, tool calls, and agent behavior in real time. It can flag, redact, block, or route risky activity for human review while keeping every risk, decision, action, and owner connected in a traceable record.
You can connect through documented SDKs or supported Desktop Agent paths. AIBIM is currently free through a controlled beta.
We’re early, so honest feedback would mean a lot:
Which AI runtime risks are hardest for you to see today?
Which integrations should we prioritize?
What would make you trust this in your production AI stack?
Thanks for checking out AIBIM.
About AIBIM AI on Product Hunt
“Runtime security for AI apps and agents”
AIBIM AI was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #145 on the daily leaderboard. AIBIM is free AI runtime security for LLM apps and agents. Monitor prompts, responses, tool calls, and agent behavior in real time. Apply policies to flag, redact, block, or route risky activity for human review. Keep every risk, decision, action, and owner connected in a traceable review record. Connect through documented SDK and supported Desktop Agent paths. Free access is currently available through a controlled beta.
On the analytics side, AIBIM AI competes within Developer Tools, Artificial Intelligence and Security — topics that collectively have 995.6k followers on Product Hunt. The dashboard above tracks how AIBIM AI performed against the three products that launched closest to it on the same day.
Who hunted AIBIM AI?
AIBIM AI was hunted by Rizacan TUFAN. 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 AIBIM AI including community comment highlights and product details, visit the product overview.
Rizacan TUFAN
Hey Product Hunt — I’m Rızacan, maker of AIBIM.
I built AIBIM because teams are shipping LLM apps and AI agents faster than they can answer basic runtime security questions: What did the model receive? What did it return? Which tools did the agent call? Why was risky activity allowed or blocked?
AIBIM monitors prompts, responses, tool calls, and agent behavior in real time. It can flag, redact, block, or route risky activity for human review while keeping every risk, decision, action, and owner connected in a traceable record.
You can connect through documented SDKs or supported Desktop Agent paths. AIBIM is currently free through a controlled beta.
We’re early, so honest feedback would mean a lot:
Which AI runtime risks are hardest for you to see today?
Which integrations should we prioritize?
What would make you trust this in your production AI stack?
Thanks for checking out AIBIM.