RAXE Runtime Security

Govern what AI does after the model responds.

Know what AI is doing in your environment, govern what it is allowed to do, and produce the evidence your security and compliance teams need.

Security Leadership Technology Leadership AI / Product Leadership Risk & Compliance
Three Control Surfaces
One control layer across AI traffic, agent behavior, and runtime execution.
The walkthrough below shows the same AI runtime from three distinct viewpoints: provider traffic, in-app intent, and machine-level behavior.
AI Security Gateway

Find shadow AI early

See provider routes, unapproved endpoints, and policy boundaries before unmanaged AI traffic becomes a blind spot.

Application SDK

Understand tool intent

Inspect prompts, tool calls, arguments, and session context where the agent actually makes decisions.

Host Sensor

See what really executed

Confirm what actually executed — which workloads ran, which files were read, and where data left the environment.

01
The Visibility Gap

AI risk begins when the agent leaves the chat window.

Models now call tools, query systems, and trigger workflows. Most controls stop at the prompt or the provider request. That leaves teams blind to what an agent actually attempted, what executed, and where the resulting traffic went.

Shadow AI Sensitive tool use Unknown workloads
Without runtime visibility, security and AI leaders cannot explain what happened, why it was allowed, or how to roll out controls safely.
02
AI Security Gateway

See and govern where AI traffic goes.

Shadow AI and unmanaged provider usage create blind spots that leadership cannot defend in a review. The Gateway sees every provider route, destination domain, and policy boundary across managed and unmanaged AI traffic. It detects unapproved endpoints and flags policy drift before exposure grows. Security teams get the evidence to approve, restrict, or investigate usage without changing application code.

Provider traffic Destination domain Policy boundary Budget and key controls
Start at the boundary when you need immediate visibility into unmanaged AI usage without changing application code.
03
Application SDK

See what the agent is actually trying to do.

Risky tool calls happen after the prompt, where most controls have no visibility. The SDK instruments the application layer to see the tool name, arguments, permissions, and session context behind every agent decision. It detects sensitive data access, privilege misuse, and unapproved actions at the point of intent. Teams get the context to review, approve, or block before the action completes. Deploy with pip install raxe.

Prompt content Tool name Arguments Permissions Session history
Prompt filtering is not enough. To govern agents, teams need the application context around the tool decision itself.
04
Host Sensor Runtime Coverage

See what actually executes on the machine.

Unknown AI workloads running on hosts and containers create risk that application-level controls cannot see. The Host Sensor monitors the process chain, workload identity, file access, and network egress at the machine level. It detects unapproved containers, suspicious execution patterns, and data leaving the environment. Investigation teams get the machine-level record that closes the gap between agent intent and what actually executed.

Workload identity Process chain File access Network egress
This is the layer that tells you what really happened after the agent decision turned into a process, a file read, or a network connection.
Why Three Surfaces
Gateway

Where did traffic go?

See providers, routes, domains, and policy boundaries for managed and shadow AI usage.

Application SDK

What did the agent try to do?

See prompt context, tool intent, arguments, permissions, and session-level escalation.

Host Sensor

What actually executed?

See workloads, process chains, file access, and egress after the model decision becomes runtime behavior.

Gateway explains the route. SDK explains the intent. Host Sensor explains the execution.
05
How RAXE Decides

Known threats, ambiguous actions, novel behavior. One verdict with the context to act.

RAXE evaluates each AI action against known policy issues, scores ambiguous intent, and flags novel behavior that has not been seen before. These signals combine into one governed decision with the rationale, posture, and evidence needed to investigate or act.

Allow Log Review Block Escalate
RAXE handles everything from known-bad patterns to never-seen-before behavior without forcing teams into one detection mode.
06
Governance Output

Every decision arrives with evidence and rollout context.

Every verdict includes identity, explanation, and rollout context. That gives teams a path from visibility to enforcement without breaking adoption or forcing them into a big-bang security rollout.

Data sovereignty by architecture. All scoring runs inside your environment. No AI traffic is sent to a vendor cloud for inspection. Supports VPC, on-premise, and air-gapped deployments.
Observe
Log activity, learn patterns, and build confidence without blocking production traffic.
Supervised
Flag risky actions, add approval steps, and prove policy fit before enforcement.
Enforce
Auto-block known threats, escalate anomalies, and keep sensitive actions governed.
Splunk · Sentinel · LogScale Operating Record Audit Trail Approval Workflow
RAXE is designed to help leadership enable AI adoption with visibility, policy control, and evidence that stands up to audit and review.
Leadership Outcome

Start with visibility. Leave with a control decision.

RAXE is built for teams that need to enable AI responsibly, not just react to it. Begin at the boundary, go deeper in-app, and extend to host-level runtime coverage as your program matures.

Boundary Visibility

See provider traffic, shadow AI usage, and unapproved routes before unmanaged AI becomes an operational blind spot.

Agent Governance

Understand tool intent, session context, and runtime behavior well enough to add approvals and policy without slowing teams down.

Audit-Ready Evidence

Give security, AI, and risk teams the action, rationale, posture, and traceability needed to defend each decision.

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Works with your existing stack — no rip-and-replace required