Control What Your Agents Do Before They Do It.

CodeIntegrity addresses a security problem that emerges the moment AI agents gain access to enterprise tools: the gap between an agent's stated intent and the actions it actually takes. When a model-driven agent calls tools to read tickets, query databases, or send emails, sensitive data enters and exits those tool calls faster than conventional security controls can observe. CodeIntegrity positions itself as the missing layer between agents and actions, providing full runtime visibility and deterministic enforcement before any tool call executes.

The platform works by translating agent instructions into sandboxed, inspectable code at runtime, making each action explicit and repeatable rather than opaque and probabilistic. A dual-LLM architecture keeps untrusted external content separated from the instruction flow, so prompt injection attacks cannot redirect tool paths or exfiltrate data. For every sensitive action the platform records the request, the source context, the destination, the policy decision, and the outcome — giving security teams an immutable audit trail without having to replay entire sessions. The platform covers tool call control, data flow control, and policy enforcement across agents and MCP clients.

CodeIntegrity is aimed at engineering and security teams in regulated industries that need to ship agentic AI products without surrendering control over how those agents touch enterprise systems and data. Its Zero Trust Control Plane binds users, agents, and MCP clients to managed identity, ensuring every action carries verified ownership. The company is SOC 2 Type II certified and offers on-premise, self-hostable deployment for organizations that require agent traffic and data to remain inside their own boundaries.