AI shouldn't see your data. So decompose what it would do into code that runs instead.
Regulated industries have data that shouldn't enter AI systems. Scrubbing 2GB and feeding it in just gives you 2GB a human can't validate. The Airlock works differently: the AI decomposes its analysis, pattern extraction, and summarization into an algorithm. The algorithm runs on the data. The output is small enough for a human to review for regulated content before anything crosses back to the model.
It's baked into our security monitoring product. Connectors decompose API analysis into code that produces structured events. Detectors decompose pattern recognition into code that produces findings. The AI never sees the raw data. It produces the algorithms, the algorithms reduce the volume, and a human reviews what's left.
Analysis, pattern extraction, summarization. Decomposed into code the user can run independently.
On the sensitive data, in the restricted environment. 2GB in, structured summary out. Volume reduced by orders of magnitude.
The reduced output is small enough to actually read. Does it contain regulated data? PII? Source material? Human makes the call.
Reviewed output feeds the next iteration. The AI refines the algorithm based on what came back. The loop compounds.
The Airlock is the pattern. These tiers govern where it runs.
Standard vendor API terms. AI reads docs and schemas, generates connectors blind. Your data stays local.
Your AI vendor, your environment, your terms. We bring the tooling.
Private deployment in your hyperscaler. No shared tenancy. Teardown at end.
Your equipment, your network. Full physical isolation. Nothing crosses the boundary.