OpenBox

What is OpenBox?

OpenBox is an AI trust and governance platform built for enterprise teams deploying autonomous AI agents at scale. As organizations rely more on agentic AI to perform real business actions — querying databases, calling APIs, sending emails, executing code — the risk of unverified, unauthorized, or opaque AI behavior grows dramatically. OpenBox solves this by providing a turnkey SDK that connects to your existing AI systems in a single integration step. Once connected, it enforces real-time identity verification for agents using Decentralized Identifiers (DID), applies configurable governance policies at the protocol level, cryptographically records every agent action for auditability, and scores dynamic risk levels per agent interaction. It fills the governance gap that security, compliance, and engineering teams face when AI agents operate across multiple systems without consistent oversight.

How to use OpenBox?

1. Generate an OpenBox API key from the dashboard and install the OpenBox SDK into your existing AI agent infrastructure with a single command.
2. Configure governance rules and policies — define which agent identities are trusted, which actions are permitted, and what risk thresholds trigger alerts.
3. OpenBox runs as a runtime layer alongside your agents, intercepting and verifying every action against your configured identity and policy rules in real time.
4. Monitor the unified dashboard for live visibility into all agent actions, risk scores, policy violations, and cross-system interactions as they happen.
5. Use the cryptographic audit trail and compliance reports to demonstrate AI governance to regulators, auditors, or internal stakeholders.

Core Features

• Decentralized Identity (DID) for Agents — Assigns and verifies cryptographic identities to each AI agent, ensuring only authorized agents can act within your systems.
• Protocol-Aware Runtime Governance — Enforces governance rules at the protocol level in real time, blocking or flagging policy violations as they occur during agent execution.
• Cryptographic Verifiability — Every agent action is cryptographically signed and recorded, creating an immutable audit trail that proves exactly what AI did and when.
• Dynamic Agent Risk Scoring — Continuously calculates a risk score per agent interaction based on action type, context, and policy alignment to enable proactive risk management.
• LLM Provenance & Content Protection — Tracks the origin and integrity of AI-generated content so you can prove what model produced which output.
• Turnkey SDK Integration — Connects to existing AI agent infrastructure with a single SDK install and no architectural changes required.
• Unified Governance Dashboard — Provides a real-time view across all agent actions, system interactions, policy violations, and risk scores in one place.

Use Cases

• Enterprise AI Compliance — Legal and compliance teams using OpenBox to ensure their AI agents operate within regulatory boundaries and can produce evidence of governance for audits.
• AI Agent Security — Security engineers deploying OpenBox to prevent unauthorized agents or compromised agentic workflows from taking damaging actions in production systems.
• Multi-agent Workflow Trust — Platform teams building complex multi-agent pipelines who need each agent's identity and actions to be verified before being trusted by downstream systems.
• AI Content Provenance — Media and publishing organizations using LLM provenance tracking to prove the origin of AI-generated content and protect against misattribution.
• Agentic AI Incident Response — DevOps and SRE teams using the cryptographic audit trail to investigate what an AI agent did during an incident, replicate the decision sequence, and prevent recurrence.