Our perspectives on securing agentic systems in the enterprise.
Enterprise AI is moving from prompts and answers to long-running agents with permissions, tools, data access, and decision authority.
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Agents need governed non-human identities that inherit from humans, narrow by task, and expire by default. Otherwise agent access collapses into shared service accounts with better language models.
Attribution sounds like a log lookup. In an agent world it is a hard correlation problem: the human, the agent, the approval, and the action live in separate systems with no shared key. Forge reconstructs the chain per platform, with deterministic rules where the format is known and LLMs where it is not.
The same agent action can be routine or a breach depending on context, so the right policy can only be derived from real behavior. Securing agents is a data and analysis problem: capture what agents do, fuse it with process, network, and identity, and automate the hardening loop.
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