Geordie enables you to understand, secure and control your agentic operations, giving you the confidence to transform how your business works.
And dozens more
Existing tools were designed to evaluate individual transactions at a point in time. Agentic risk is sequential, cross-surface, and continuous.
EDR and NDR alone don’t give teams the context or controls to govern agent behavior across machine-to-machine workflows.
Cloud security doesn’t give teams enough control over agent workflows that span cloud, code, endpoint, APIs, and third-party services.
IAM stops at access decisions, while agent security requires visibility and control over how that access is used.
MCP gateways struggle to scale when teams need low-friction controls across multi-tool agent operations.
That’s more than a coverage gap.
It’s an architectural mismatch.
What agents do we have, and what can they reach?
Geordie discovers every agent and maps their full configuration: permissions, tool and MCP connections, knowledge sources, system prompts, models, and sub-tools, updated continuously as they change.
What are the agents actually doing?
Geordie provides a continuous, auditable record of every prompt, plan, response, and tool invocation, with behavioral baselining and anomaly detection built in.
What risks does this create?
Geordie analyzes your full agentic environment using proprietary risk and threat modeling, automatically mapping findings to standards including OWASP, NIST, ISO42001, the EU AI Act, and AIUC-1.
What is all of this costing us?
Geordie connects agentic spend to the actual work and business outcomes it produced, identifying where spend is wasteful, and remediating it through the same system teams use for security.
What do we do to control these risks?
Beam intervenes directly at the agent level in real time, delivering deterministic controls without gateway latency, alongside advisory mitigations for teams who want human oversight in the loop.
Geordie’s inline remediation engine, Beam, shapes agent behavior in real time through context engineering, deployed via agent-native and harness-native mechanisms including lifecycle hooks, plugins, and MCP. Responses are context-specific and escalate with risk.
Beam watches the action and writes it to the immutable record without touching it. The agent proceeds exactly as it would have, and the team gets the evidence it needs to decide whether anything stronger is warranted.
Beam writes additional context into the agent’s reasoning and offers an approved pathway. Nothing is blocked; an agent heading somewhere it is not authorized for is guided to an equivalent it is, and the work continues.
A new mode for the Claude ecosystem. The agent stops and waits for an explicit decision to continue or not. Beam delivers the context behind the pause to the agent, so whichever way the operator decides, the agent carries that context into what it does next.
Lifecycle hooks are binding. Prohibited actions and tool use do not execute, and the attempt is written to the immutable record.
Forge adopted AI across the business faster than any inventory could keep up with. Geordie gave their security team a live picture of every agent running on endpoints, in developer tooling and across AI platforms, then turned that picture into the inherent-versus-residual risk numbers the board already works from.
90%
of Forge's tech ecosystem covered
Inherent vs residual
AI risk quantified in financial terms, reported to the executive team
A singular view of agent spend, across platforms, arranged however you need it. Analyze spend in context, connecting the cost to the work that it produced. All from the same behavior-based evidence bank you use for security.
Cost IntelligenceTake control of AI agent uncertainty
Get a single source of truth for every autonomous agent your organization runs.
“We're seeing the iceberg that rocked the Titanic — weeks in advance rather than the moment it appears on screen. We're able to take a snapshot of the entire ecosystem and have adult, grown-up conversations about what's responsible and what's not. We can quantify everything now.”
