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Diagrid Catalyst 2.0 Brings Cryptographically Verifiable, Durable Execution to Ten AI Agent Frameworks

Diagrid's Catalyst 2.0 adds Dapr-based cryptographic attestation and automatic failure recovery for AI agents across ten frameworks, including LangGraph and Microsoft Agent Framework.

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Overview

Diagrid announced Catalyst 2.0 on 28 July 2026, adding automatic failure recovery and cryptographic verification to AI agents built with ten frameworks, including LangGraph, Microsoft Agent Framework, Google Agent Development Kit (ADK) and Dapr Agents, according to InfoQ. The release combines durable execution — automatically resuming interrupted agent runs from the point of failure — with verifiable execution, cryptographically signing each step of an agent’s workflow history, according to Diagrid.

What We Know

  • Developers add a Diagrid code package directly into their existing agent framework rather than rewriting applications or switching frameworks. Diagrid represents model and tool calls as durable workflow activities so interrupted runs resume without repeating completed work, according to InfoQ.
  • The failure mode Catalyst targets is a familiar one: when a long, multi-step agent run fails late in the sequence, and there is no checkpointing at individual-call granularity, a retry re-executes every model call that already completed, according to InfoQ.
  • Ten framework integrations ship in the release: LangGraph and LangGraph Deep Agents, Microsoft Agent Framework, Google Agent Development Kit (ADK), AWS Strands, OpenAI Agents SDK, Claude Managed Agents, CrewAI, Pydantic AI Agents and Dapr Agents, according to Diagrid.
  • Catalyst runs in cloud, on-premise and fully air-gapped environments. Durable agents are built with a Python SDK, while workflow SDK support extends to .NET, Go, Java, JavaScript and Python; the open-source Dapr 1.18 SDKs also add Rust, according to InfoQ.
  • The verification model is built on Dapr 1.18: Dapr hashes batches of workflow-history events, links each digest to the preceding signature, and signs the result using the Dapr sidecar’s SPIFFE-based identity. The signed chain is checked when workflow state loads, making deleted, reordered or modified history detectable, and receivers validate each signed chunk against the Dapr Sentry trust anchor so histories can be verified outside the application that produced them, according to InfoQ.
  • Dapr groups this work into three capabilities — Workflow History Signing, Workflow History Propagation and Workflow Attestation — with the latter two carrying verified execution context across workflow and service boundaries, according to InfoQ.
  • Signing is disabled by default in Dapr 1.18, gated behind the WorkflowHistorySigning feature flag and dependent on mTLS, with daprd refusing to start if signing is enabled while mTLS is off. It is also a one-way decision per workflow: there is no retroactive signing of existing history, and toggling signing on a workflow already in progress triggers a verification error, according to InfoQ.
  • “The first wave of AI focused on making models intelligent, but the next wave is all about making AI systems trustworthy,” said Yaron Schneider, co-founder and CTO of Diagrid and chair of the Agentic AI Foundation Workflows Working Group. “When an AI agent triggers a tool, calls a service, or hands work to another agent, organizations need proof of what happened and confidence it will finish the job,” according to Diagrid.
  • “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, CEO and co-founder of Diagrid, according to Diagrid.
  • ZEISS Group is named as an early adopter. “In a rapidly evolving landscape of AI models and frameworks, Catalyst provides the stable foundation we can rely on,” said Wendelin Niesl, Head of End-to-End Core Application Engineering at ZEISS Group, according to Diagrid.
  • Diagrid says Catalyst delivers up to ten times the performance of open-source Dapr and can support millions of concurrent agent workflows, according to Diagrid. Diagrid’s pricing spans a free cloud tier, dedicated-cloud and bring-your-own-cloud plans sized by concurrent workflows, and a custom-quoted Enterprise Server edition for on-premise and air-gapped deployments, according to InfoQ.

What We Don’t Know

  • InfoQ notes that Diagrid’s “up to ten times” performance claim does not specify whether the multiple refers to throughput, workflow starts per second or latency, nor which workload, hardware or Dapr configuration it was measured against, meaning the comparison cannot be independently assessed, according to InfoQ.
  • Cryptographic attestation proves the integrity and provenance of recorded workflow history, not that an agent made a correct decision, a tool returned accurate data, or that every external side effect was captured, according to InfoQ.

Analysis

Catalyst is not the first durability layer built for these frameworks. LangGraph’s own persistence layer records checkpoints at graph superstep boundaries and offers persistent task execution through its Agent Server, while Temporal and Restate already provide replay- or journal-based execution for long-running applications and can host agent workflows, according to InfoQ. What differentiates Catalyst, per InfoQ’s analysis, is a single Dapr-based recovery and attestation model that spans several frameworks at once, applying durability to individual model and tool calls rather than to graph-level checkpoints, according to InfoQ.

Diagrid frames verifiable execution as a compliance and security play aimed at regulated industries: the company says security teams can confirm an agent did what it claimed to do, compliance teams get a chain of custody for every decision, and organizations under regulatory requirements can prove execution was completed, trace its origin, and confirm it was not altered, according to Diagrid. Diagrid, the company behind the open-source Distributed Application Runtime (Dapr) and a leading maintainer of the project within the Cloud Native Computing Foundation, says organizations in financial services and healthcare already use its platform to orchestrate multi-agent workflows and enforce fine-grained data access, according to Diagrid.