What we do.

Prompt injection. Tool misuse through adversarial inputs. Data exfiltration through model outputs. Memory poisoning. Model-to-model trust abuse in multi-agent chains. These aren't theoretical — they're the failure modes that get exploited in systems that passed standard security review.

We assess agentic systems specifically for this class of vulnerability. And we use agentic tooling in our own assessments — automated recon, vulnerability chaining, and continuous scanning that runs faster and finds more.

They work in demos, then break under real conditions — malformed tool outputs, loops that don't terminate, memory that bleeds between sessions, models that hallucinate when the retrieval layer returns nothing useful. Most teams discover this after shipping.

We design for failure from the start. Orchestration with explicit failure modes, evaluation harnesses that run in CI, and infra that surfaces problems before users do.

An agentic system shipped without knowledge transfer becomes a liability — no one knows why it makes the decisions it makes, how to debug it when it breaks, or how to extend it without introducing new failure modes.We run multi-day programs built around your real systems and real codebase, not toy examples. Engineers leave capable of designing, evaluating, debugging, and extending agentic software independently.