An operating system keeps track of everything running on a machine. We built a Technology Value OS that does the same for your cloud and AI: every resource tied to who owns it, what it costs, and whether it still earns its keep. It is launching on Product Hunt on 30th June 2026.
It's 2 a.m. An engineer spins up an 8-GPU cluster to test one idea. It works. They go to bed. The cluster doesn't. It keeps running, burning roughly $750 a day while doing nothing. Three weeks later, finance finds a $24,000 charge nobody recognizes and starts asking who owns it. By then the money is gone.
The surprising part was never the bill. It was that nobody knew who owned the cluster. No owner, no accountability, no one to notify, so no one ever shut it down. This happens with GPUs, but also cloud instances, SaaS seats, AI endpoints, and forgotten experiments that quietly keep charging.
An operating system, but for what your technology costs
An operating system keeps track of everything running on a machine: every process, what it uses, whether it is still needed. A Technology Value OS does the same thing across everything you run: your cloud, your AI, and your SaaS.
It ties every resource to three facts that usually live in three different heads: who owns it, what it costs, and whether it still earns its keep. That is the whole idea. Cloud, AI, and the humans who own them, in one accountable system.
This is not a cost dashboard with a new name. A dashboard reports a number and walks away. An operating system governs what runs.
Knowing the number does not change the number
Identifying waste and removing it are two different jobs, and almost every tool only does the first. A dashboard is an expensive smoke detector that cannot put out the fire.
Watch what happens to a waste report after it lands in an inbox. In week 1, about 30% of items get acted on. By week 4 it drops to roughly 5%. By month 3 it is effectively 0%. The list goes stale, the resources keep billing, and a new report gets generated on top of the old unfixed one. The real cost is the distance between knowing and fixing.
The fix is a closed loop, not a louder alert
The system runs a closed loop: detect, decide, act, verify. It discovers your estate across AWS, GCP, and Azure, ranks fixes by real impact, acts with guided and one-click remediation across 20+ certified rules, then verifies the change actually held.
That last step matters more than it sounds. Most automation marks a task complete when the API call returns. This marks it complete when reality agrees: it waits for the resource to reach target state before it says done. The whole cycle runs in under five minutes, because when acting is slower than ignoring, people ignore.
Acting on production needs a brake, not just a gas pedal
The reason teams do not automate remediation is fear, and the fear is rational. So every action passes through a blast-radius classification first.
Low-blast-radius fixes run with no human in the critical path: deleting an orphaned disk, stopping an instance with zero traffic for 30 days, scheduling non-prod to sleep nights and weekends. High-blast-radius actions wait for approval. Safe work moves at machine speed; risky work keeps a person in the loop. Every decision, automatic or approved, is written to an audit log. No black-box calls in the dark.
One estate: cloud, AI, and SaaS
Accountability only counts if it reaches everything: cloud across AWS, GCP, and Azure, Databricks, the GenAI estate across AWS Bedrock and GCP Vertex AI, idle and orphan cleanup, non-prod scheduling, anomaly detection, and IAM. One loop, one set of guardrails, every owner named.
So the forgotten cluster from the start does not get three weeks. It surfaces the moment it appears, routed to the person who spun it up, with a fix they can approve in one click.
What waste goes unowned in your stack right now? That is the question worth answering before the next $24,000 surprise.
We are putting this on Product Hunt on 30th June 2026. If the ownerless gap looks familiar, come say hi. Originally published on zop.dev.
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