Govern Enterprise AI Agents at Runtime

Enable enterprise-developed and third-party AI agents to safely access data, tools, and enterprise systems while maintaining governance, security, and operational control.

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Enterprise Agent Ecosystem
Support Agent
Finance Agent
Coding Agent
HR Agent
Ops Agent
Use Case

The Enterprise AI Agent Challenge

Enterprises are deploying AI agents to access data, invoke tools, interact with systems, and execute business workflows autonomously. As agents become operational actors, they introduce new governance, security, and compliance challenges. Most agent frameworks provide orchestration. Paradigm provides governance, security, and observability.

Unauthorized Data Access & Exposure
  • Accessing enterprise data without identity-aware controls
  • Retrieving information users are not authorized to access
  • Amplifying insider risk through autonomous actions
Uncontrolled Tool, MCP & Autonomous Actions
  • Accessing MCP servers, APIs, and enterprise tools without governance
  • Executing workflows that violate enterprise policies
  • Performing actions without required approvals or validation
Unmanaged Models & Agent Ecosystems
  • Unapproved model usage across clouds and AI providers
  • Lack of centralized governance over AI services
  • Increased security, cost, and agent-to-agent coordination risks
Lack of Visibility, Provenance & Compliance
  • Limited visibility into agent decisions, prompts, and tool calls
  • No lineage across workflows and autonomous actions
  • Difficulty demonstrating compliance, explainability, and audit readiness

Enterprise AI agents require runtime governance across identity, data, tools, models, and actions. Not just monitoring after deployment.

The Paradigm Approach

Unified Runtime Governance for Enterprise AI Agents

Paradigm provides a unified governance, security, and observability layer for enterprise-developed and third-party AI agents, enforcing policies across data access, tool execution, workflows, and autonomous action before they occur.

Paradigm integrates into enterprise-developed and third-party agents through APIs, providing governance, security, and observability while preserving your existing architecture.

Built for Enterprise Agents

Whether You Build or Buy, Paradigm Governs

For organizations building agents internally or adopting third-party agent platforms, Paradigm provides a unified governance, security, and observability layer across agent ecosystems.

Custom Built Agents
Microsoft Copilot
Salesforce Agentforce
OpenAI Agents
CrewAI
LangGraph
AutoGen
MCP-Enabled Agents
The Business Impact

Deploy Enterprise AI Agents with Confidence

Accelerate Agent Deployment
Deploy enterprise-developed and third-party AI agents at scale while maintaining governance, security, observability, compliance, and cost control.
Reduce Operational Risk
Prevent unauthorized data access, unsafe tool execution, policy violations, and uncontrolled autonomous actions before they occur.
Maintain Visibility & Compliance
Maintain complete visibility, auditability, and explainability across agent decisions, actions, workflows, and data access.
Govern Agents Through a Single Control Plane
Whether you build agents or buy agents, Paradigm applies consistent governance, security, and observability policies across models, tools, MCP servers, clouds, and enterprise systems.
Control Agent & Model Costs
Monitor model usage, tool consumption, token spend, and agent activity to optimize costs and maximize ROI across enterprise AI deployments.
Deployment & Integration

Any Use Case With Choice of Agent Architecture, Cloud, And Model

Paradigm integrates with your agent stack, whether you're building on open-source frameworks, using third-party agent platforms, or developing custom architectures. We provide the governance layer regardless of how you build.

Broad Range of Agent Frameworks & Platforms
Model Provider Agnostic
Seamless Enterprise Integration
Flexible Deployment Models
SaaS · VPC · On-Premises · Hybrid
Time to Value
Weeks to production (vs. 6-12 months building governance in-house).

Ready to Govern Enterprise AI Agents at Scale?

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