Agentic identity
Securing AI Identity on the Agentic Web
Securely identify and continuously monitor autonomous AI systems to prevent fraud, ensure compliance, and build trust.
Securely identify and continuously monitor autonomous AI systems to prevent fraud, ensure compliance, and build trust.
Model Context Protocol (MCP) standardizes how AI agents connect to tools, APIs, and data sources. But it focuses on interoperability, not identity or accountability. That means when an agent initiates a transaction or accesses sensitive data, there's no standardized way to verify who that agent is, whether it's authorized to act, or how to trace its actions back to accountable parties.
Without identity verification, agents can hallucinate to access sensitive data, trigger unauthorized actions, or move freely inside private systems.
Binding AI agents to verified human owners turns risky autonomous actions into trusted, accountable, and compliant interactions.
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Agent activity can be detected through the Trust Graph network across human (web/mobile) and agent-oriented surfaces (machine-to-machine protocols).
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Incode links each AI agent to a verified human, requiring high-assurance identity checks before sensitive data is accessed or critical actions are taken.
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Incode issues a secure identity token to the agent once ownership is verified, which then links all subsequent actions back to the verified owner.
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Incode continuously monitors AI agent activity patterns to detect anomalies or deviations from expected behavior, preventing misuse before it escalates.
Agent activity can be detected through the Trust Graph network across human (web/mobile) and agent-oriented surfaces (machine-to-machine protocols).
Incode links each AI agent to a verified human, requiring high-assurance identity checks before sensitive data is accessed or critical actions are taken.
Incode issues a secure identity token to the agent once ownership is verified, which then links all subsequent actions back to the verified owner.
Incode continuously monitors AI agent activity patterns to detect anomalies or deviations from expected behavior, preventing misuse before it escalates.
As agents begin making decisions on behalf of people and systems, trust is essential. Incode verifies who or what an agent is, protecting identities and ensuring accountability.
Built for trust, Incode is uniquely positioned to secure the agentic world.
AI-Resistant Biometric Capture
As synthetic agents and deepfake identities multiply, Incode’s biometric capture prevents AI-generated spoofs from entering the system. It gives developers and networks a reliable way to anchor agent identities in real, verified humans.
Solve agentic identity challenges with secure solutions and propel customer trust.
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