How does it work with frameworks like LangChain or CrewAI?

It provides an OpenAI-compatible API/SDK that sits on top of the control plane. Developers use their favorite tools and frameworks as normal, while Prediction Guard enforces governance policies underneath.

Is this just another AI gateway?

No. If an AI gateway is a door, Prediction Guard is the building's entire security and management system. It provides the underlying infrastructure for zero-trust control, supply chain management, and runtime governance that a simple gateway lacks.

What kind of governance policies can be enforced?

It can enforce custom policies aligned with frameworks like NIST AI RMF, OWASP Agentic Top 10, and the EU AI Act. Policies can block agent behavior, control supply chain access, and define runtime rules.

How is it deployed and what's the infrastructure impact?

It's designed to be self-hosted within your own network boundary. The control plane is described as lightweight and runs beside your agents to ensure sovereign control.

Can I build agents directly with it?

Yes, via Agent Forge. You can deploy both interactive and autonomous agents using API or natural language prompts, with key systems integrated via MCP.

How does it achieve the claimed 4x TCO reduction?

By consolidating multiple fragmented 'AI security' point solutions into one comprehensive control plane, eliminating redundant services, licensing, and integration overhead.

Directory/Automation/AI Governance/Prediction Guard

Prediction Guard

Prediction Guard is a self-hosted AI control plane that provides governance, observability, and security for AI agents and models within an enterprise's own infrastructure. It operates on zero trust principles, enforcing policies on agent behavior, supply chain, and data flow to prevent unauthorized actions and data leakage. The platform consolidates AI management, offering a single control plane to build, deploy, and monitor agents while ensuring compliance with standards like NIST and OWASP. Key capabilities include an Agent Forge for quick agent creation via API or prompts, an OpenAI/Anthropic/MCP-compatible API that works with popular frameworks like LangChain and Crew AI, and comprehensive runtime governance. It targets platform engineers, AI engineers, and software vendors in regulated industries who need to scale AI agents without losing control, reducing TCO and accelerating production timelines.

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Added on

Sep 22, 2026

Self-hosted AI control planeZero Trust agent securityRegulated enterprisesUnified governance APIMCP compatibleIn-boundary deployment

Product information

Everything worth knowing about Prediction Guard

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Agent Forge

Deploy interactive and autonomous AI agents via API or natural language prompts. Integrates key systems via MCP and tracks human + agent identities with built-in governance.

Unified API/SDK

A single API compatible with OpenAI, Anthropic, and MCP protocols. Works with popular frameworks like LangChain, Crew AI, and OpenAI SDKs while enforcing governance.

Zero Trust Control Plane

A lightweight control plane running inside your own infrastructure for sovereign control over agent behavior, supply chain, observability, and cost. Ensures least agency and limits blast radius.

Runtime Governance

Prevent agents from operating off-script and enforce custom policies in real-time during execution.

Supply Chain Management

Control what agents can access and limit your blast radius by governing the tools and models they use.

Technical capabilities

In-Boundary Deployment

The entire platform runs within your own infrastructure, ensuring data sovereignty and compliance with regulated enterprise environments.

Policy Enforcement Framework

Governance harness enforces policies at the system level without requiring end-users or agents to make the 'right' decisions.

Must watch videos

Prediction Guard | Zero Trust for AI Agents

3:11

Tutorial3:11

Prediction Guard | Zero Trust for AI Agents

EP14: Transform Your Engineering Org with Agentic Coding While Enforcing Strict AI Governance

28:08

Tutorial28:08

EP14: Transform Your Engineering Org with Agentic Coding While Enforcing Strict AI Governance

If your engineering organization isn't adopting agentic coding tools like Claude Code or Cursor, they are getting left behind. Developers are eager to integrate these tools into their workflows, because they see the clear productivity gains. However, organizations remain concerned about these tools operating in an uncontrolled manner where they could take destructive action (deleting databases), accumulate huge usage costs, and introduce vulnerabilities into repositories. In this focused, 30 minute session, we demonstrate how to enforce AI governance on top of tools like Claude Code with Prediction Guard. We show how to control and monitor usage of these agentic coding tools without negatively impacting the developer experience. What We Cover: • The Agentic Development Blueprint: An introduction to modern agentic coding workflows and the surrounding agent harnesses. • Seamless Governance Enforcement: An architecture for seamlessly connecting your agentic coding tools into production grade AI governance enforcement. • Live Demo: A real time look at common developer interactions powered by agentic coding tools with full governance enforcement and observability. Key Takeaways: • The Competitive Necessity of Agentic Tools: Organizations that hesitate due to safety concerns risk being left behind by faster-moving competitors. • Balancing Speed with Control: The primary barrier to adoption isn't developer interest, but organizational risk. The solution presented is a governance layer (via Prediction Guard) that monitors and controls these agents without creating friction for the developer. • A Blueprint for Production-Grade Governance: Adopting AI agents isn't just about downloading a tool; it requires a specific architectural approach. 🎙️ Featuring: Daniel Whitenack, CEO of Prediction Guard 📅 Originally aired: July 14, 2026 🔗 Learn more: https://www.predictionguard.com

30:43

Tutorial30:43

EP13: The Intelligent ERP

Transforming Retail, Manufacturing, and Tech with Secure NetSuite AI Integration Recent Oracle NetSuite releases mark a major shift towards AI-ready ERP systems with, for example, the NetSuite AI Connector. Embedding a connection to NetSuite into AI agents promises to transform critical financial and operational workflows. However, for enterprises in regulated industries, the connection of AI to critical ERP systems is not merely a pursuit of efficiency but a high-stakes compliance challenge. This sort of integration necessitates absolute transparency and control over sensitive ERP data. In these environments, robust governance enforcement ensures that connections to systems like NetSuite facilitate innovation without compromising the ironclad security and auditability standards. 🎙️ Featuring: Daniel Whitenack, CEO of Prediction Guard 📅 Originally aired: June 2, 2026 🔗 Learn more: https://www.predictionguard.com

Who uses it

Real use cases, no hype

Regulated Enterprise AI Deployment

Deploy and govern LLMs and generative AI behind the firewall in high-compliance industries.

AI Agent Lifecycle Management

Build, deploy, and enforce runtime policies for both interactive and autonomous agents.

Multi-Framework AI Integration

Govern and manage AI projects built with LangChain, CrewAI, and OpenAI SDKs through a single control plane.

Supply Chain Security for AI

Control and limit agent access to tools and external services to reduce blast radius.

AI Observability & Cost Management

Maintain full visibility into agent actions, tool calls, policy violations, and model costs.

Platform Engineering for AI

Provide total visibility and control for AI systems without data leakage.

AI Software Vendor Embedding

Embed comprehensive AI governance capabilities into your own software product.

What's great

Massive TCO reduction (claimed 4x) by consolidating fragmented AI security.
Claimed 300% faster time-to-production for AI agents.
Compatible with major frameworks (LangChain, CrewAI, OpenAI SDK).
Self-hosted, sovereign deployment for regulated enterprises.

Technical strengths

True zero-trust, in-boundary control plane for agents.
Unified API/SDK for OpenAI, Anthropic, and MCP compatible with existing stacks.
Enforces comprehensive AI governance (NIST, OWASP, EU AI Act).

Where it falls short

Self-hosted model adds operational overhead for deployment and maintenance.
Primarily focused on governance and control, not the AI model itself.
Requires integration with your existing infrastructure and stacks.
Effectiveness relies on proper policy definition by the user.

Technical limitations

Complexity in managing the full control plane lifecycle.
Potential vendor lock-in to Prediction Guard's specific governance harness.
Success claimed (e.g., 300% faster) is context-dependent on 'fragmented' starting points.

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

It's a self-hosted AI control plane that sits in your infrastructure. It provides governance, security, and observability for all your AI models, tools, and agents from a single, sovereign system.

Traffic Insights

Monthly Visits

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October 2026

Growth Rate

vs last month

Dominance

in Automation

Top Country

—

Top Countries Breakdown

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Growth Trend

Stable

Traffic has remained stable.

Pricing overview

Paid Pricing

Prediction Guard Pricing

Prediction Guard uses a paid pricing structure. Real-time rates, custom enterprise quotas, and plan details are managed directly on their official platform.

Check Pricing on Prediction Guard

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