Describe your feature.
What does it do? What should a good run look like? Tell Sam in plain words. Review the checks Sam proposes.
Sam from Ops · Your AI operations teammate
Your AI systems have someone watching out for them.
Tap Sam to say hello again
Tell Sam what your AI is for.
Sam watches what it does, explains what matters,
and follows through—with your permission.
Every agent adds more to watch. Human attention doesn’t grow with them.
A loop looks busy. A job runs twice. A source goes quiet while its dashboard stays green.
Sam pays attention to whether your AI is doing its job, so you can focus on the work only you can do.
Other tools ask which numbers matter. Sam asks what the feature is meant to do, then proposes checks for you to confirm.
What does it do? What should a good run look like? Tell Sam in plain words. Review the checks Sam proposes.
Two light hooks (and soon a small SDK) report timings, sizes, tokens and shape. Your prompts and replies stay in your app.
Sam notices a change, explains the evidence, brings it to the owner and follows up. After a fix, Sam checks that it worked.
Observe. Explain. Own. Respond. Verify.Finding the problem is only the beginning.
These scenes come from workloads we built and ran.
They are examples, not customer
stories. Sam’s replies are scripted, and some of these checks are still coming.
A local example only. Your text isn’t sent or saved.
Scripted examples of Sam’s reports. This page isn’t connected to an application or a live AI service.
Sam is AI. “Someone paying attention” describes the job Sam does. You decide what Sam can watch, say and do.
Sam receives timings, sizes, token counts and a fingerprint of each call. Never the prompt or reply. The fingerprint is one-way: it shows Sam a pattern, never the words.
Sam runs on the Sam platform, separate from the systems being watched. Messages go out only through channels you connect.
Choose observe, recommend, ask first or act, per action and environment. Sam cannot approve Sam’s own requests. Actions are recorded; approvals expire.
Sam keeps observations, suspicions and recommendations apart. “Healthy” means healthy on the checks Sam runs. Insufficient visibility is called out.
Sam’s numbers, findings and stop decisions come from code. The model helps phrase answers and draft checks. Sam is watched by the same checks Sam runs on your systems, within a budget you set.
Keep them. Sam comes to the person who owns the problem, with the reason and the evidence, then keeps the thread through follow-up and verification. Related events stay together, and you control the messaging policy, all the way to silence.
Waste costs time instead of a per-token bill. Sam watches time, queues and throughput, including one agent slowing down others on shared hardware.
Today, halting is a switch you turn on or off for your workspace. With it on, a detection can return a halt to your agent. Asking you first, per action, is coming. A halt is a request your agent must honour, not a guaranteed stop or hard spending cap.
That’s what the inspector SDK is for. It’s coming. It will report fingerprints and shape numbers without sending content, and on someone else’s device, nothing is sent until that person agrees. More about the SDK
A key for each feature, with its description. Nine signals, each finding shown with its evidence, in the Sam dashboard. Per-feature detection settings and a halt switch you control. See which signals work today
Checks proposed from your feature description, email notifications, owner threads and follow-up, asking before acting, verifying a fix, the fingerprint codebook, the inspector SDK, Sam’s chat, Slack and Teams, local hardware monitoring, adoption reporting and a feature’s view across environments.
We believe the people building with AI should be able to trust what they have built, without watching it every minute.
Sam learns what your AI is for, watches what it does and follows problems through to a verified fix, within the authority you grant.
Give your AI a teammate