One security loop
across your AI stack
Prompt injection
Malicious instructions override intended behavior.
One security loop
across your AI stack
Continuously test, guard, and trace LLM applications, agents, and workflows — from first adversarial test to every runtime decision.
claims-assistant / eu-central
The threat is no longer only what the model says. It is what the agent can access, trigger, reveal, and repeat.
Malicious instructions override intended behavior.
Private context appears in prompts, outputs, or tools.
An agent acts beyond the permission or intent it needs.
A valid request reaches the wrong downstream action.
One policy and evidence model across the AI lifecycle.
Automated adversarial testing for prompts, retrieval, tools, and agent behavior. Turn findings into release gates and runtime policies.
Explore PoliRail TestInspect prompts, context, outputs, and tool calls before they become business actions.
Explore PoliRail GuardSearch prompts, context, policy decisions, tool calls, and reviewer actions as one evidence chain.
Explore PoliRail TraceSee the intent, context, policy, tool request, reviewer action, and evidence record without reconstructing them across separate systems.
Protect conversations, retrieved data, and downstream actions.
Separate trusted instructions from untrusted retrieved context.
Constrain tool access by role, intent, and environment.
Preserve controls and evidence for security and governance teams.
PoliRail supports technical risk programs aligned with leading AI security and governance frameworks. Alignment is not certification.
“Can we prove this agent was tested before release?”Composite research insight / Application Security
“Can we stop one unsafe action without disabling the entire workflow?”Composite research insight / AI Platform
“Can we reconstruct the decision for an audit or incident?”Composite research insight / Risk & Governance
Bring one LLM application, agent, or workflow. We’ll show how Test, Guard, and Trace create a continuous security loop.