Diagrid Catalyst 2.0 adds durable execution to more than 10 agent frameworks

Diagrid Catalyst 2.0 adds durable execution to more than 10 agent frameworks Agent infrastructure startup Diagrid Inc. today released Catalyst 2.0, an update to its managed workflow engine that adds automatic failure recovery and cryptographic verification to artificial intelligence agents built on frameworks such a LangGraph, Microsoft Agent Framework and Google’s Agent Development Kit. Developers do not have to rebuild anything to use it. Teams add a Diagrid code package to the framework they have already standardized on, and their existing agent workflows gain durable execution without any change to how the agents were written. Agent failures are expensive. Most frameworks offer no built-in guarantee that a long-running workflow will recover and finish once something breaks, which leaves humans to step in, burns tokens on repeated work and stalls projects. Catalyst 2.0 pairs durable execution, in which an agent resumes from the exact point of failure, with verifiable execution, in which each step is cryptographically signed and traced back to its source. Diagrid offered LangGraph as an example. It provides strong orchestration but only basic checkpointing for recovery, the company said, leaving detection and recovery logic to developers. Run on Catalyst 2.0, those same workflows complete after a failure with no custom recovery code. Supported frameworks in the release are LangGraph and LangGraph Deep Agents, Microsoft Agent Framework, Google Agent Development Kit, AWS Strands, OpenAI Agents SDK, Claude Managed Agents, CrewAI, Pydantic AI Agents and Dapr Agents. The verification side comes out of Dapr 1.18, released in June, and covers cryptographic history signing, execution lineage propagation and workflow attestation. Security teams get a way to confirm an agent did what it claimed to do, and compliance teams get a chain of custody for each decision, which matters most in regulated sectors where execution has to be proved complete, traceable and unaltered. Catalyst 2.0 runs in the cloud, on-premises and in fully air-gapped environments. Diagrid claims it improves on open-source Dapr performance by up to 10 times, enough to support millions of concurrent agent workflows. “Every AI agent framework released in the past two years has made it easier to build agents, but none have made it easier to trust them in production,” said Mark Fussell, co-founder and chief executive of Diagrid. “With Catalyst 2.0, developers keep the framework they’ve already chosen, and they gain the durability and verifiability that production AI systems require. That combination is what turns a prototype into something an enterprise can actually run.” Yaron Schneider, Diagrid co-founder and chief technology officer, who chairs the Agentic AI Foundation’s workflows working group, framed the release as a move past the first wave of AI, in which the goal was making models intelligent, toward making agent systems trustworthy. German optics manufacturer ZEISS Group is an early user. Wendelin Niesl, its head of end-to-end core application engineering, said Catalyst gives the company a stable foundation for building a durable platform for both AI and traditional workloads as models and frameworks keep shifting. The creators of Dapr and KEDA founded Diagrid in 2021. Diagrid is a leading maintainer of Dapr within the Cloud Native Computing Foundation. The company has raised $24.2 million in venture capital funding, most of it in a 2022 Series A led by Norwest Venture Partners. 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