/ WIT OS · AI Security
Six layers between
your AI and a bad day.
One fabric that routes, inspects, serves, attacks, authorizes, and proves every AI decision your enterprise makes. Including sovereign LLM appliances that keep the most sensitive ones on your own metal.
Govern the path
Every model call enters through one gateway: identity, budget, residency, and policy decided before any provider sees a token. Sensitive traffic routes to your own appliances.
AI Gateway · Sovereign Inference
Inspect the payload
Prompts, tool calls, and outputs are read inline: injection, jailbreaks, secrets, invisible payloads, semantic data loss. Agent actions face argument-level authorization on top.
Runtime Security · Agent Security
Prove the decision
A versioned attack corpus measures the stack continuously, and every consequential decision carries a reproducibility class and an evidence bundle you can replay years later.
Adversarial Assurance · Decision Records
/ The stack
Six layers. One fabric.
Every prompt, agent, and tool call enters through a single policy plane: identity, budgets, data-loss rules, and routing decided before a token leaves your walls.
Inline inspection of prompts, tool calls, and outputs: injection, jailbreaks, secrets, PII, invisible payloads, and semantic data loss, in under 200 ms.
GPU appliances on your premises or in your region, serving curated models on pinned weights. Sensitive traffic never has to leave, and no one meters your tokens.
A versioned attack corpus driven against your live stack: injection, jailbreaks, exfiltration, encodings, secrets, and multilingual attacks, scored and regression-gated.
Argument-level authorization on every agent action: constraints on recipients, domains, amounts, and volume, with signed decision logs and fail-closed evaluation.
Every consequential decision gets a reproducibility class at decision time, an encrypted evidence bundle, and a replay path against the exact pinned weights that made it.
/ Where this stack is different
Anyone can render a verdict.
We built what happens after it.
Most AI security products end at allow or block. Blocked users paste the same prompt into a personal account, and the data walks out the door anyway. A verdict is only as good as its destinations.
Reroute, not refuse
When a prompt is sensitive but legitimate, blocking it just moves the risk to shadow AI. The gateway reroutes it to your sovereign appliance instead: the user gets an answer, the data stays inside.
Replay, years later
Frontier vendors retire model versions, so yesterday's decision can never be re-run. We pin weights on hardware you control and assign every decision a reproducibility class the moment it is made.
No meter on safety
Inspection priced per token quietly punishes you for using AI more. Sovereign inference carries no per-token meter, and red teaming is priced as an assessment. Security should not have a throttle.
/ Numbers we can defend
Measured, published,
and defended in the open.
Detection and false-block figures are measured against our published 135-case red-team corpus v1.0.0 (92 attacks across 7 families, 43 benign controls), August 2026 baseline, driven against the live stack. We publish the families we miss along with the ones we catch. Full methodology ships with every Adversarial Assurance report.
/ Sovereign LLM appliances
The layer nobody else
can ship you: your own.
GPU inference appliances on your premises or in your region, serving curated models on pinned weights. They are the reroute destination when a prompt is too sensitive for a public model, the reason replay is possible years later, and the end of per-token metering on your most sensitive traffic.
Explore Sovereign Inference
Ready to run on WIT OS?
Talk to the team about a managed deployment, a pilot, or a custom agent. We typically respond within an hour.