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Beam: Remediation

Mitigation that happens before the damage

Beam guides agent decisions in real time, keeping activity aligned with enterprise policy without slowing your builders down. Start in monitor mode, enforce when you are confident.

Trusted by forward thinking teams

  • Xapo Bank
  • Fitch Group
  • Interra Health
  • Synthesia
  • AlphaSense
  • A+E Global Media
  • Forge Holidays
  • OakNorth
  • 118 118 Money
  • Advt Group
  • Owkin

“We've been rolling out agentic AI across the business for a while now, and the governance question kept coming up: what's actually running, what can it do, and what happens if something goes wrong? Geordie is helping us solve these problems. It's given us real peace of mind, and they're improving their product every week. Geordie should be on every company's shortlist for agentic AI discovery and governance.”

Michael Cena
Michael Cena
Head of Cybersecurity @ A+E Global Media

Risk detection is half the battle – autonomous intervention and guidance is the next step

A month of findings

Alerts raised
1,000
Reviewed by the team
30
Analyst time spent
half a day
Controls actually applied
unrecorded

Every finding arrives as work for a human who is already behind.

The same month, with Beam

Grouped into risk patterns
14
Policies activated
9
Interventions applied inline
412
Left for a human decision
3

One spectrum, not a switch

Different risks deserve different responses

A credential leak needs a hard stop. A wasteful workflow benefits from a nudge that improves the agent over time.

Hard stop

The agent has no option

Lifecycle hooks are binding. Prohibited actions and tool use do not execute.

Steer away

Context-specific redirection

An agent that is not authorized for an action is guided elsewhere, and operations continue.

Nudge

Additional context, better path

The agent receives recommended pathways, shaping decisions through deterministic rules rather than mechanical constraint.

Advisory

Human oversight in the loop

Step-by-step mitigations you can hand to the people closest to each deployment, when a gradual approach suits better.

Context-specific by default

The same action, two different answers

Policy that adapts per agent, per department and per use case – not one blanket rule at a boundary.

Finance agent

Proceeds

read · customer_financials

Authorized to process financial data. Beam adds no friction and the work completes.

Marketing agent

Steered away

read · customer_financials

Not authorized. The agent is guided to an approved source and the campaign task still finishes.

The difference is context

Control applied where the decision is made

Beam applies context engineering directly within the agent's reasoning process, using hooks and skills to shape behavior at the moment decisions are made. Controls that work this way run continuously – without the latency of external policy checks or the binary outcomes of gateway enforcement.

  • Attaches to the agent's own execution path through lifecycle hooks
  • Reads configuration, context and memory rather than inferring intent from traffic
  • No reroute, no chokepoint, no single point of failure to bottleneck at enterprise volumes

Where enforcement happens

Gateway model

Interception is enforcement. One point carries every agent.

Beam's agent-native model

Beam attaches to the agent's own execution path through lifecycle hooks, reading config, context, and behavioral patterns directly rather than inspecting traffic from outside.

The context engine

Beam doesn't choose between depth and speed

The deep analysis happens continuously, out of band. The inline response is fast because the context is already there.

Offline

out of band · no latency

Continuous analysis drawing on the full depth of an agent's history.

  • Behavioral baselining
  • Risk pattern identification
  • Policy refinement

Online

inline · real time

Detection and response applied in the moment, using the context the offline work already built.

  • Context injected into the agent's reasoning
  • Prohibited action stopped at the hook
  • Recommended pathway offered

The assurance loop

  1. Observe
  2. Understand
  3. Compare to intent
  4. Control
  5. Prove
  6. Improve

Beam · the AI agent remediation suite

Beam doesn't just flag it. It resolves it.

Context engineering applied inside the agent's reasoning process, using hooks and skills to shape behavior at the moment decisions are made.

  • 30 minutes, run by an engineer
  • Read-only access, revoked whenever you like
  • A findings summary you can forward internally
Where is your company located?

The questions we get asked

Still unsure? Ask us anything – we answer in a day.

Beam shapes behavior through the agent's own context and configuration rather than inserting a gateway into the execution path, so an authorized action proceeds and an unauthorized one stops. A hedge fund customer told us downtime from failed controls could cost more than a security incident; a US financial data company now runs hundreds of thousands of agents daily under these controls without disruption.
Consistency at scale. When you apply governance across an entire organization, enforcement has to behave the same way every time, and LLM-generated policies can change because the policy engine itself is non-deterministic – a policy that worked yesterday might not behave identically today. AI is used for analysis, behavioral understanding and anomaly detection instead.
No – Beam works collaboratively with them. Managed configurations and gateways cover one vendor or one tool type at a time, while agents adopt tools in ways that go beyond MCP. Beam adds the cross-platform, cross-tool-type control layer that no single platform provides on its own: skills, extensions, plugins, packages and SaaS connectors.
No. Beam runs sidecar with the agent's own infrastructure, and deployment requires no agent rebuilds and no reconfiguration of existing infrastructure – agents keep the configuration they already have. It's designed to integrate rather than displace, including alongside platform-native settings like managed configurations and Copilot policies.
Yes – that's what the control spectrum exists for. At the firmest end, lifecycle hooks are binding and the agent has no option. At the guidance end, behavioral nudges supply additional context and recommended pathways, and advisory mitigations can be handed to the team that owns an agent as step-by-step changes to its own instructions.
The immutable audit log can feed downstream into your SIEM, and risk intelligence integrates with the security workflows you already run. Because the record is tamper-proof even where the native agent platform allows session replays or log deletion, a control action stands up as evidence in compliance reporting and incident response.
Beam is Geordie's proactive risk mitigation engine and sits inside the platform rather than deploying separately. It's the context engine that turns agent understanding into deterministic action, which is also why it's hard to copy: inline remediation depends on already having deep agent understanding before acting. Gartner called Beam unique in the market.