We build AI agents that hold up under attack.
And we fix the ones that don't. Injection paths, over-scoped tools, silent failures — found, closed, monitored.
Three ways agents fail — and what we build against.
The failures that don't show up in your tests — until an attacker or a customer finds them first.
Injection paths
Prompt injection hidden in retrieved documents and tool outputs — the vector your query-only guardrail never sees. We find the paths into your agents before they're used to exfiltrate data.
Over-scoped access
Agents with more permission than the task needs. We map every tool call, credential, and boundary an agent can cross — and close the ones that turn a bug into a breach.
Wrong, with a 200 OK
A confident wrong answer, and no alert fires. We instrument the evals and drift detection that catch the failures your monitoring misses.
Open research on production AI.
Working papers, code, and benchmarks. Released as we publish.
Three steps. From assessment to armed.
Scoped to your stack. Independent, because we didn't build it.
Assess
We map your live agents, RAG, and SLMs and find the injection paths, over-scoped tools, and silent failures. Prioritized findings report at the end.
Remediate
We fix what we found — guardrails, scoped permissions, eval gates — and verify the fixes hold in production.
Monitor
Drift and injection monitoring, monthly reviews, and we hold the pager when something new shows up. You ship features.
What's in your agent's context that a customer can write to?
Book a call. Whether you're building an agent or hardening one that's already live, we'll scope the work in 30 minutes — attack paths and fixes, not a slide deck.
