Enterprise AI security, governance, and LLM protection for secure AI adoption.
- Prompt override attempt
- Cross-app access check
- Policy escalation event
Krioa Security gives organizations an enterprise AI security platform for AI applications, LLM traffic, and secure agentic workflows. Centralize AI governance, improve auditability, inspect AI traffic, and move from experimentation to production deployment with stronger confidence.
Enterprise AI security for teams that need real controls, not just AI policy statements.
Krioa Security helps enterprises control AI at the points where risk actually appears: LLM requests and responses, MCP tool execution, and agent runtime behavior. Instead of relying on scattered controls, teams can inspect, approve, ground, and audit AI activity from one platform.
What the platform actually does in production AI environments.
Krioa Security combines enforcement, approval, grounding, and audit features into one operating layer so security teams can govern real AI traffic and agent behavior without inventing separate control systems.
Inspect prompts and responses before they reach the model.
Route LLM traffic through a security pipeline that can block, flag, or allow requests based on policy and risk.
Hold sensitive actions for review before execution.
Use Human-in-the-Loop queues and approval paths when a request or tool action needs a person in the loop.
Limit answers to approved knowledge when accuracy matters.
Back responses with trusted documents and citation-aware retrieval instead of letting models improvise unsupported answers.
Three distinct control layers for LLM traffic, protocol mediation, and agents.
Each product focuses on a different part of the AI stack, so teams can secure model interaction, tool execution, and multi-step agent behavior with the right controls in the right place.
Proxy AI traffic through a policy-enforced inspection layer.
Inspect prompts and responses, apply security modules, and control how AI applications interact with external models.
MCP ProxyIntercept MCP tool calls before they reach real systems.
Mediate protocol-connected workflows with inspection, access boundaries, and safer tool exposure.
Secure Agentic AI RuntimeControl agent sessions, tool execution, delegation, and approvals.
Govern multi-step agent workflows with runtime checks, approval paths, and auditable execution records.
Inspect LLM prompts and responses with a 20-module security pipeline.
Put security in front of live model traffic, not just around it. The gateway gives teams a place to enforce prompt and response controls before AI output reaches users or downstream workflows.
- Prompt and response inspection before model execution
- Policy-driven block, allow, and escalation behavior
- Support for internal assistants and customer-facing AI applications
Mediate MCP tool access before tools run against real targets.
MCP-connected systems should not become an ungoverned side door into enterprise tools. Krioa Security places a proxy layer between clients and upstream servers so tool use can be inspected before execution.
- Intercept MCP
tools/callrequests before execution - Reduce unsafe protocol exposure and tool-surface sprawl
- Support safer connected workflows without direct runtime exposure
Apply runtime controls to agents before autonomy turns into drift.
Secure agent behavior with controls that operate during execution, not just during design reviews. The platform can validate tool parameters, govern delegation, and route risky actions into approval flows.
- Governed tool-call interception and validated parameters
- Recursion-depth and blast-radius runtime limits
- Human approval paths and immutable action history
Support enterprise AI programs across industries, teams, and operating needs.
The platform is relevant anywhere organizations need stronger governance, clearer visibility, and better operational control around AI usage.
Escalate sensitive actions into Human-in-the-Loop approval queues.
Preserve human decision points when high-risk prompts, tool actions, or agent steps should not run automatically.
Keep an immutable Action Ledger for review, audit, and investigation.
Give security and compliance teams a durable record of control decisions, approvals, and execution paths.
Use approved internal documents to support safer, evidence-backed answers.
Reduce unsupported output by grounding AI responses in trusted knowledge instead of free-form model behavior.
What teams gain when controls are tied to real platform behavior.
The value is practical: fewer blind spots, clearer approvals, and stronger evidence when security, compliance, and platform teams need to explain how AI is being used.
Common questions about AI security, MCP security, and agent governance.
A quick overview of what Krioa Security is built to control across LLM applications, MCP-connected tools, and agentic workflows.
What does Krioa Security protect?
Krioa Security helps protect LLM prompts and responses, MCP tool calls, and agent runtime behavior with enforcement, review, grounding, and audit controls.
Can teams review risky AI actions before they run?
Yes. Human-in-the-Loop queues can hold sensitive prompts, tool executions, and agent actions for operator review before they proceed.
Can the platform limit answers to approved internal knowledge?
Yes. Trusted Knowledge Base support helps ground answers in approved documents when unsupported model output is not acceptable.
Bring AI adoption under a more secure operating model.
Review the platform, explore the control surface, and connect your stakeholders around a more governable path to enterprise AI.