Demo

Control AI risk. Before it runs ahead.

Noqoro acts as a hidden control layer for enterprise AI. It continuously maps AI activity, identifies emerging exposure, validates risk, and guides the controls needed to protect sensitive systems, data, and workflows.

Copilots Agents Workflows Prompts MCPs Chatbots

Solutions

Point each use case at the right control layer.

Short, focused solution paths keep the story clear and the page light.

Discovery

Find active AI and shadow use.

Map copilots, agents, and unmanaged paths before they drift into risk.

Validation

Test prompts, tools, and delegated actions.

Reveal the paths attackers can chain, bypass, or misuse.

Governance

Turn findings into controls and proof.

Translate exposure into owners, guardrails, and evidence.

Operating Loop

Observe. Analyze. Validate. Defend.

The product flow stays simple: map AI, analyze exposure, validate paths, and defend live systems.

Observe Analyze Validate Defend

Services

Support the move from pilot to governed scale.

Focused services keep the page light and the next step clear.

Assess Start with one workflow or one agent.
Plan Define controls, owners, and next steps.
Scale Move from pilot security to governed rollout.

AI DISCOVERY & RECON

Map the AI estate before exposure spreads.

Discover active copilots, agents, prompts, tools, RAG paths, model endpoints, and workflows. Recon shows how those assets connect to data, users, tools, memory, and business systems.

ATTACK VALIDATION

Confirm what can actually be abused.

Run controlled validation against prompts, RAG context, tool calls, agent actions, and orchestration flows so security teams can separate confirmed exploitability from theoretical findings.

RISK SCORING

Prioritize risk by exploitability and impact.

Score AI risk using exposure paths, control state, data sensitivity, tool permissions, blast radius, and validation outcomes so teams know what to fix first.

POLICY CONTROLS

Connect AI findings to enforceable controls.

Map AI exposure to policy expectations, routing rules, control owners, remediation actions, and retest requirements so defenses stay tied to real AI behavior.

REPORTING

Give teams the right view of AI risk.

Create security, governance, and leadership-ready views that show exposure, validated risk, remediation progress, control status, and evidence coverage.

CONTINUOUS VALIDATION

Keep AI controls current as systems change.

Recheck high-risk agents, prompts, tools, data paths, and workflows as AI systems evolve, so control drift is detected before exposure becomes impact.