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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

​Questera is an agentic customer engagement platform that enables growth and lifecycle teams to define strategies and execute them faster than ever. Users can create custom AI agents or utilize pre-configured ones for effortless personalization, auto-segmentation, journey automation, hands-free campaign execution, and reporting, allowing for limitless scalability. It offers a simple four-step process to create AI agents: define the agent by entering key details such as name and image; add core instructions specifying goals, rules, and parameters; choose abilities like email automation, segmentation, and retargeting from over 75 integrations; and finally, test and deploy the agent with real-time feedback. Alternatively, users can get started quickly by employing Questera's preconfigured agents, such as Sara, the smart ads retargeting agent, who crafts personalized ads to re-engage visitors and launch impactful retargeting campaigns.

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

Businesses interested in a solution to automate growth and retention without requiring an expensive in-house data science team

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

Questera
Founded: 2022
United States
www.questera.ai/

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Categories

Categories

Integrations

Amazon S3
Amplitude
Braze
Google Ads
Google Cloud Platform
Looker
Mixpanel
Salesforce
Segment
Snowflake
WhatsApp
Zapier

Integrations

Amazon S3
Amplitude
Braze
Google Ads
Google Cloud Platform
Looker
Mixpanel
Salesforce
Segment
Snowflake
WhatsApp
Zapier
Claim Calljmp and update features and information
Claim Calljmp and update features and information
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