Enterprises are discovering that keeping AI agents running is only half the problem. As agents gain access to business systems and operate across increasingly long workflows, organizations face a more difficult question: how to prove that every action an agent takes was permitted, recorded, and recoverable.
To address that challenge, OpenBox AI and Temporal today announced an integration that embeds governance directly into the runtime layer used to execute AI agents. By combining Temporal’s durable execution platform with OpenBox’s authorization and attestation capabilities, enterprises can ensure that long-running agents are not only reliable but accountable.
Industry analysts expect governance concerns to become one of the biggest obstacles to AI agent adoption. Gartner predicts that by 2027, 40% of enterprises will scale back or abandon autonomous agents because governance failures emerge only after production incidents.
At the same time, organizations are confronting a growing gap between experimentation and production. Agents increasingly operate across systems such as Salesforce, Snowflake, GitHub, Slack, and internal applications, yet many enterprises lack mechanisms to verify whether actions were authorized, approvals were preserved, or complete audit trails exist.
“Reliability for production agents has a clear answer. Temporal has become the infrastructure many organizations trust to keep long-running workflows alive,” said Tahir Mahmood, co-founder of OpenBox AI. “The next question customers ask is how to ensure agents only do what they’re supposed to do. By bringing governance directly into the runtime, every action becomes provable by default.”
The integration automatically injects governance checks into Temporal workflows, evaluating every execution, activity, and signal before actions occur. Policies can allow, constrain, require approval, block, or halt operations. Human approvals survive failures and restarts, while cryptographic attestations and immutable audit logs provide a continuous evidence trail.
The approach allows governance to scale alongside agents rather than relying on separate monitoring systems or manual reviews after incidents have already occurred.
“As AI agents take on real work inside enterprise systems, the bar for what ‘production-ready’ means has fundamentally changed,” said Johann Schleier-Smith, Technical Lead for AI at Temporal. “Combining durable execution with runtime governance means every action is authorized, recorded, and recoverable, so organizations can move AI into production with confidence.”
The integration is available immediately for developers building on Temporal.
