Agentic safety and security require a new language for interacting with intelligent systems.
Catch 100% of prompt injections by design. No guesses, just security.
Our latency measures in microseconds. We secure multiple I/O with unnoticeable overhead.
Get full observability over stateful reasoning backing every decision. Enforce safe behaviours under every circumstance
Traditional AI safety relies on probabilistic filters and post-hoc moderation, methods that fundamentally cannot guarantee protection against adversarial inputs. Lycid enforces security through reasoning graphs.
Every tool call, every data dependency, every information flow is tracked and validated against a formal security policy before execution.
The result is a framework where safety is a mathematical property of the system, not a best-effort heuristic.
Agentic AI systems make chains of decisions that are opaque by default, hidden inside token sequences and internal state. Lycid makes reasoning visible and structured.
By representing agent workflows as explicit data-flow graphs, each node is a concrete operation: a tool call, a data transformation, a decision branch, with tracked provenance and taint labels.
This graphical intermediate layer lets you inspect, audit, and constrain how an agent reasons before it acts. Instead of trusting a black-box chain-of-thought, you get a formal reasoning structure that can be verified, bounded, and governed.
As agentic systems grow in complexity, they become vulnerable to subtle cognitive failures that can be exploited by attackers.
Belief drift, goal hijacking, or coordination failures between agents are silent threats that wonβt be revealed by injection filters.
Lycid can trace causal influences in agentic workflows and provide principled visibility over these cognitive vulnerabilities in real time.
Join forward-thinking enterprises protecting their AI systems