Real-Time Agentic Security

Stop hoping. Start proving.

See how enterprises and AI builders use HikmaAI to close the gap between deployment and security.

If you want to start from who you are instead, the solutions page does that. Compare by audience

Shadow AI & Improper Behavior

The ban is a false sense of security.

Telling employees not to use AI does not stop them — it just stops you from seeing it. The agents are running either way.

Scenario 01

Shadow AI Discovery

Detecting invisible AI traffic patterns — such as employees bypassing corporate bans using personal accounts — and bringing them under official security policy.

Scenario 02

Developer Toolchain Control

Monitoring developers using autonomous coding assistants to prevent the accidental leakage of sensitive client data or proprietary logic into public prompts.

Agents That Go Out of Bounds

The agent is doing exactly what it was told.

Most agent incidents are not bugs. The agent followed its instructions — the instructions, or the inputs, were the problem.

Scenario 01

Preventing Data Exfiltration

Using the Intelligent Gateway to enforce domain allow-lists, ensuring agents cannot be manipulated into making unauthorized API calls or exfiltrating data via tool-calls.

Scenario 02

AI Spend Circuit Breaker

Enforcing per-key budget caps and model restrictions to stop "runaway" agents from creating massive cost explosions before the invoice arrives.

Trust & Accountability for AI Builders

Enterprise buyers are demanding proof before signing.

If you sell agentic products, the security questionnaire is now part of the deal. The question is whether you answer it with a promise or with evidence.

Scenario 01

Accelerating Enterprise Adoption

How proprietary inference providers use HikmaScore™ and Red Teaming reports to provide the independent security certification that enterprise buyers demand to close deals.

Scenario 02

Securing the Agentic Pipeline

Providing a safety "trust signal" for autonomous agents before they are shipped to clients, significantly reducing liability for the AI builder.

High-Stakes Regulated Environments

The liability is undefined — until a regulator asks.

In regulated settings, the accountability question is dormant, not absent. It becomes urgent the moment something goes wrong.

Scenario 01

The Digital Employee Accountability Chain

Creating a verifiable "HR file" and decision log for customer-facing agents to meet MiFID II and EU AI Act transparency requirements.

Scenario 02

Synthetic Identity & KYC Protection

Monitoring and red-teaming KYC agents to detect and block synthetic identity attacks (deepfakes/fake voices) used for financial fraud.

These are the scenarios.

If you'd rather start from who you are — an AI builder, a regulated enterprise, a public sector team — the solutions page is organised that way.

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