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Nuggets lets AI agents act with provable authority across systems and organizational boundaries. It gives you a trust layer for humans, organizations, machines, and AI agents. When something happens, you can prove who did it, on whose behalf, and under what authority. This matters when you need to deploy autonomous AI in production environments that require accountability, auditability, and compliance. For context on why autonomous systems break traditional identity models, see Background: The Trust Gap in Autonomous AI.

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Why Existing Identity Systems Fall Short

Traditional IAM was built for humans logging into systems. AI agents don’t work like that. They run continuously, use multiple tools, cross cloud boundaries, and often act for several people or teams at once. This breaks the basic questions enterprises need to answer:
  • Who or what acted?
  • On whose behalf?
  • With what authority?
  • Under which policy?
  • Can this be proven later?
When you can’t answer these questions, AI projects don’t make it to production.

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What Nuggets Adds

Nuggets upgrades and works across your existing IAM, PAM, and cloud infrastructure. It doesn’t replace access control. Instead, it adds cryptographic trust on top - attaching verifiable identity, intent, consent, and policy to actions. Every action generates durable cryptographic proof you can use for audit, compliance, and investigation. Autonomous actions become provable by default.

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How Nuggets Works

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Trust That Travels With Every Action

An agent gets a verifiable identity linked to a human and organization. Each action carries declared intent, applicable policy, and required consent. Nuggets evaluates authority in real time. Every action generates cryptographic evidence of what happened. From decision to execution, actions are auditable while remaining privacy-preserving.

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Core Control Primitives

Nuggets provides foundational control primitives for production AI systems: Identity
Cryptographically verifiable identity for every actor - humans (KYC/KYE), organizations (KYB), machines (KYM), AI agents (KYA). Intent
Verifiable declaration of what an agent is authorised to do and under what constraints. Consent
Durable, provable consent that travels with actions across systems and organizations. Policy
Policies that apply consistently across clouds, tools, and identity providers. Accountability
Full provenance for every action: who acted, under what authority, with what outcome. Compliance
Privacy-preserving audit and investigation capabilities aligned with regulatory expectations.

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Works With And Upgrades Your Existing Stack

Nuggets sits on top of what you already have. Your IAM keeps managing access. Your hyperscaler keeps securing workloads. Your enterprise security tools stay in place. Nuggets adds a cross-cloud trust layer for autonomous actions that existing systems weren’t designed to handle.

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Common Use Cases

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Enterprise AI Operations

Deploy internal AI agents across HR, finance, customer service, and operations with provable authority and auditability.

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Regulated Workflows

Meet regulatory expectations for provenance, consent, and investigation as AI systems act autonomously.

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Agent-to-Agent and Agent-to-System Interaction

Establish trust across agent frameworks, APIs, MCP, and legacy systems without shared identity infrastructure.

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How to Use These Docs

The docs are organized around trust primitives and system behaviour, not products. You’ll find:
  • Conceptual explanations of agent identity, authority, and provenance
  • APIs and SDKs for issuing and verifying trust
  • Integration patterns with IAMs, hyperscalers, and agent frameworks
  • Examples for enterprise, regulated, and cross-boundary deployments
If you’re evaluating Nuggets, start with the conceptual sections. If you’re building, go straight to APIs and integrations.

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From Pilots to Production

Autonomous AI only scales when it can be trusted. Nuggets makes AI actions provable, auditable, and compliant by default.