Every enterprise wants AI everywhere. None can afford to lose track of what it reads, what it spends, or what it does.
One engine reads the intent of your data and your AI in real time, and puts you in control at the three points you can lose it. It readies your data before AI touches it, routes every workload to the model that fits, and governs every prompt and agent as it acts.
We are working closely with a first group of enterprises putting this into production. There is room for a few more.
Models are already reading your documents, answering your customers, and increasingly acting on their own through agents. What has not kept up is the ability to know what those systems are touching, what they are costing you, and whether you can stop them when they overstep. So enterprises face a bad trade, slow down to stay in control, or move fast and hope.
Intent is the missing piece, not just what a request contains, but what it is for and what it is about to do. Read that in real time, and control stops being a wall of rules you hope holds.
One engine reads it at three points in the same pipeline, and each is a point where control would otherwise slip.
It reads your data at rest, so you know what you hold before AI touches it.
It reads each workload in motion, so it goes to the model that fits.
It reads every prompt and agent as it acts, so nothing crosses a line you have drawn.
Data Lens reads your data wherever it lives, across drives, clouds, and applications, and works out what you hold, what is sensitive, and what is exposed. Then it acts, writing that understanding back into the files as labels and closing the access that should never have been open.
Most enterprises send every request to one frontier model and pay frontier prices for all of it. Intent Router understands what each request needs and routes it to the cheapest model that is approved and capable, so most work runs on leaner, faster models and the frontier is saved for what earns it.
Once AI is running, the risk moves from what it knows to what it does. Intent Gateway reads every prompt, response, and agent action against your policies and what your data holds, and allows, flags, or blocks each one in milliseconds. It reads an agent's plan before the tools run, so a harmful action is stopped at the intent to take it, not after the damage.
Stop agents at the plan, not at the damage.
The first problem is knowing what your data is. Card numbers, contracts, medical records. Everyone treats this as solved. It is not, the tools that claim to read them still miss anything messy. We are more accurate, on the same benchmarks, by a wide margin.
The second problem is knowing what your data is for. Whether it belongs in that prompt. What an agent means to do with it. That is intent. It is harder, it is the part AI actually turns on, and we are the only ones reading it.
An engine like this is not assembled from parts. It is why others build on ours instead of building their own.
The same engine behind our products can be shaped into a custom model for your specific problem. We build it with you, you run it in your own environment, and we keep it updated for its life.
Explore Model Foundry →The thinking behind the platform, in public. Where enterprise AI is heading, what we are learning from real deployments, and the research that shapes what we build. Three of the latest below.
The fastest way to understand Cyvia is to see it read your own data and your own traffic. We will show you on a live environment, then talk about where you are and what you need.