ZizkaDB

ZizkaDB

Zizka AI SL
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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

ZizkaDB by Zizka AI is an operational intelligence database for production AI agents. The platform helps teams understand why an agent behaved a certain way by capturing decisions, causal lineage, session replay, and behavioral drift. ZizkaDB gives developers tools to replay agent sessions end to end, compare behavior against a baseline, and detect regressions before users notice. It supports Python SDK, TypeScript SDK, Cursor MCP, native tools, REST API, open source self-hosting, and managed cloud deployment. Teams can use ZizkaDB to investigate prompt changes, skipped tool policies, inconsistent answers, and costly retry loops. Built for AI engineering teams, ZizkaDB helps debug production agents faster and improve agent reliability with clearer operational visibility.

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

ZizkaDB is best suited for AI engineering teams, agent builders, platform teams, developers, startups, enterprises, ML engineers, DevOps teams, and organizations that need agent observability, session replay, causal lineage, behavioral drift alerts, time travel, production debugging, semantic history search, MCP integration, self-hosted infrastructure, managed cloud, and cross-agent fleet monitoring

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

Free
Open Source
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 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 4.0 / 5

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.

Pros & Cons from Real Users

Pros

  • has amazing feature which are required for this phase of ai development zika db has everything in it

Cons

  • would appreciate if support is upgraded currently its limited

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

Zizka AI SL
Founded: 2026
Spain
zizka.ai

Alternatives

Alternatives

Categories

Categories

Database Features

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Integrations

CrewAI
Docker MCP Gateway
LangChain

Integrations

CrewAI
Docker MCP Gateway
LangChain
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