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About

Calljmp is a developer-first AI agent runtime designed to build, run, and scale long-running stateful workflows written in TypeScript. While many modern tools like Mastra AI provide rich frameworks to define agents and workflows, Calljmp focuses on actually running them reliably in production. Calljmp combines agent logic, durable execution, human-in-the-loop pause/resume, retries with idempotency, and built-in observability into a unified execution environment. Developers implement agents as code, and the runtime guarantees reliable execution, state persistence, and operational visibility without gluing together custom queues, databases, and monitoring stacks. Calljmp is ideal for engineering teams, product developers, and backend architects who want to embed intelligent agents into product systems while offloading execution complexity to a purpose-built runtime.

About

Red Hat Runtimes is a set of products, tools, and components for developing and maintaining cloud-native applications. It offers lightweight runtimes and frameworks (like Quarkus) for highly-distributed cloud architectures, such as microservices. A collection of runtimes, frameworks, and languages so developers and architects can choose the right tool for the right task. Support is included for Quarkus, Spring Boot, Vert.x, and Node.js. An in-memory distributed data management system designed for scalability and fast access to large volumes of data. An identity management system that enables developers to provide web single sign-on capabilities based on industry standards for enterprise security. A message broker that offers specialized queueing behaviors, message persistence, and manageability. An open source implementation of the Java™ platform, standard edition (Java SE) supported and maintained by the OpenJDK community.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

SaaS Founders, CTOs, Software Engineers, AI Developers, Product Managers

Audience

Developers and companies seeking a solution for developing and maintaining cloud-native applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • Calljmp stands out as a true agentic backend for running AI workflows in production. It turns fragile, prompt-driven scripts into durable, stateful systems that can handle long-running tasks reliably. The biggest advantage is built-in durable execution. Every step in a workflow is checkpointed, so there’s no “state amnesia.” If an API fails or a process is interrupted, execution resumes exactly where it left off. This is critical for AI agents handling multi-step or long-duration jobs. It also acts as a centralized layer for execution state, retries, and observability. Instead of building custom infrastructure for each agent, we rely on Calljmp to manage orchestration and state persistence. That shift alone saves significant engineering time and reduces operational risk.
  • "Most ""AI agent"" frameworks are just brittle API wrappers. Calljmp’s biggest win is that it operates as a true managed agentic backend. It provides durable execution out of the box, saving state checkpoints at every step. If a task times out or a node restarts mid-workflow, the agent doesn't lose its place—it just resumes. This saved our team from having to manually build and maintain custom queues, state databases, and retry logic. Another massive plus: the workflows are fully replayable. Debugging complex, multi-step agents is actually possible because you get full observability into the execution data instead of dealing with an LLM black box. It handles the 80% of backend infrastructure plumbing that usually makes production AI so fragile, letting us focus entirely on the core logic."

Cons

  • Setup takes some effort since it’s a foundational backend layer - not a plug-and-play tool. You need to think in terms of architecture, not just prompts.
  • It’s a deep architectural layer, not a plug-and-play toy. Because it operates as a serious code-first agentic backend, the initial setup and integration take actual development time.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Calljmp
Founded: 2025
United States
calljmp.com

Company Information

Red Hat
Founded: 1993
United States
www.redhat.com/en/products/runtimes

Alternatives

Alternatives

Apache Camel

Apache Camel

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eve

Vercel
Karaf

Karaf

Apache Software Foundation

Categories

Categories

Integrations

Apache Tomcat
GraalVM
JCov
Java
JavaScript
Kubernetes
Node.js
Quarkus
Reactive
Red Hat Data Grid
Red Hat Integration
Spring Boot
Vert.x

Integrations

Apache Tomcat
GraalVM
JCov
Java
JavaScript
Kubernetes
Node.js
Quarkus
Reactive
Red Hat Data Grid
Red Hat Integration
Spring Boot
Vert.x
Claim Calljmp and update features and information
Claim Calljmp and update features and information
Claim Red Hat Runtimes and update features and information
Claim Red Hat Runtimes and update features and information