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Establish security controls for enterprise AI before it becomes your next attack surface

As AI systems gain access to enterprise data, tools, and workflows, CISOs need controls that extend beyond individual applications.

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Built for security leaders responsible for governing enterprise AI

Apply security controls consistently across AI systems

Enforce authentication, authorization, policy checks, and access controls across models, agents, tools

Make AI activity visible and auditable

Capture prompts, responses, tool
calls, agent actions, and policy
decisions

Control how agents interact with enterprise systems

Govern access to internal APIs, databases,
SaaS platforms, MCP servers, and
operational systems

A security control plane for models, agents, and enterprise tool access

Enforce security policies at the point of execution

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  • Route AI traffic through a centralized control layer with authentication, authorization, rate limits, and policy checks
  • Use OPA or Cedar policies to govern prompts, responses, agent actions, and MCP tool calls without requiring application teams to implement controls independently.
  • Maintain consistent enforcement across OpenAI, Anthropic, Gemini, Bedrock, Azure OpenAI, and OSS models.
AI Gateway setup page with API provider and model selection options for OpenAI and others.

Create a complete audit trail for AI activity

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  • Capture prompts, responses, tool invocations, policy decisions, user identities, timestamps, and execution metadata for every request.
  • Trace incidents from user request to model response to downstream tool execution using request-level logs and execution traces.
  • Export telemetry through OpenTelemetry into Splunk, Datadog, Grafana, and existing SIEM workflows.

Govern agent access to enterprise systems

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  • Use the MCP Gateway to control how agents access internal APIs, databases, SaaS platforms, and operational systems.
  • Issue scoped credentials, centrally manage OAuth flows, and enforce authorization policies before actions are executed.
  • Monitor and govern AI coding assistants (like Claude Code), agentic developer tools, and autonomous software engineering systems

Protect sensitive data across AI workflows

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  • Apply redaction, filtering, and policy controls before data is sent to models or downstream tools.
  • Enforce data residency requirements across model inference, agent workflows, MCP servers, failover paths, and telemetry systems.
  • Ensure security controls remain consistent as teams adopt new models, providers, and agent frameworks.

Enterprise AI workflows you can enforce and govern on TrueFoundry

SOC investigation assistants

Enable analysts to query security tools, retrieve evidence, and investigate incidents

Security triage agents

Automate alert enrichment and context gathering while maintaining full auditability and access controls.

Compliance evidence collection

Allow agents to gather logs, controls, and audit artifacts through controlled access to enterprise systems.

Identity access review assistants

Enable agents to review permissions
and retrieve identity records through
policy-controlled workflows.

Governed AI coding assistants

Govern how coding agents access repositories, CI/CD systems, secrets, and infrastructure while maintaining centralized auditability.

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For us, the TrueFoundry AI Gateway is about complete abstraction. Our applications never talk directly to model providers. We can switch models, manage throttling, and trace behavior centrally without changing code. That separation is critical as we scale agentic workflows across customers.

Rahul Bhattacharya
Co-Founder & CTO, Adopt AI
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