This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
SentinelAI is a lightweight AI safety and observability layer for LLM applications. Unlike tools focused on model evaluation or output generation, SentinelAI monitors both prompts and responses in real time, detects prompt distribution shifts, flags risky outputs, and combines multiple signals into a unified, explainable risk score. Developers can integrate it through a simple API to catch AI failures before they reach users.
Hey!!!
We're the maker of SentinelAI.
The idea came from a frustrating realization while building AI applications: we obsess over model quality before launch, but once AI reaches production, we often have very little visibility into what it's actually doing.
A model can hallucinate, leak sensitive information, get jailbroken, or behave unexpectedly, and many teams only discover it after users report it.
That felt backwards.
We monitor servers, databases, APIs, and infrastructure. Why not AI behavior itself?
So I started building SentinelAI: a platform that analyzes prompts and responses, detects risky patterns, surfaces anomalies, and helps teams understand when their AI systems may be drifting into unsafe or unreliable territory.
What started as a side project quickly turned into a bigger question:
How do we build AI systems that are not just powerful, but observable and trustworthy?
That's the problem I'm exploring with SentinelAI.
I'd love to hear your feedback, and if you're building with LLMs or AI agents, what's been your biggest challenge in monitoring them once they're go live?
Thanks for checking it out!
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About Sentinel AI on Product Hunt
“Spot Risky AI Behavior Before It Ships”
Sentinel AI was submitted on Product Hunt and earned 3 upvotes and 1 comments, placing #157 on the daily leaderboard. SentinelAI is a lightweight AI safety and observability layer for LLM applications. Unlike tools focused on model evaluation or output generation, SentinelAI monitors both prompts and responses in real time, detects prompt distribution shifts, flags risky outputs, and combines multiple signals into a unified, explainable risk score. Developers can integrate it through a simple API to catch AI failures before they reach users.
Sentinel AI was featured in SaaS (42.5k followers), Artificial Intelligence (471k followers) and Security (2.7k followers) on Product Hunt. Together, these topics include over 150.8k products, making this a competitive space to launch in.
Who hunted Sentinel AI?
Sentinel AI was hunted by nilkanth ahire. 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.
Want to see how Sentinel AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
nilkanth ahire