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ZizkaDB Review

ZizkaDB is an operational intelligence database for AI agents, providing monitoring, replay, lineage, and drift alerts to debug and understand agent behavior.

shipped Aug 10, 2026updated Aug 12, 2026developer-toolsfreemium
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ZizkaDB — product screenshot

Why it matters

1Offers a freemium model with a free self-hosted version under AGPL-3.0 license.
2Managed cloud plans start at €29 per month for 50,000 events.
3Provides Python SDK, TypeScript SDK, Cursor MCP, and a REST API for integration.
4Supports self-hosting via Docker and managed cloud deployment.

About ZizkaDB

Business Model
Hybrid (Subscription + Usage)
Headquarters
Málaga, Spain
Platforms
Web, Self-hosting via Docker
Target Audience
Teams building and deploying AI agents

Pricing Plans

Self-Hosted
Free forever
  • 1 API key
  • Your infrastructure
  • Docker Compose
  • Community support
Pro
€29/ month
  • 50k events / month
  • 3 active API keys
  • Email support
Team
€69/ month
  • 100k events / month
  • 10 active API keys
  • Priority support
Enterprise
Annual License / annual
  • Single-tenant VPC deployment
  • Up to 50 agents
  • Fleet dashboard and ranking
  • Install + integration workshop

Cost Examples

  • Up to 50k events for €29/month
  • Up to 100k events for €69/month
API DocsGitHubOpen Source

Specs

API Available

Yes, public API

overview

What is ZizkaDB?

ZizkaDB is an operational intelligence database tool developed by Zizka AI that enables AI engineering teams to monitor, debug, and understand the behavior of their AI agents. It provides features like session replay, causal lineage, and behavioral drift alerts to identify and resolve issues in production AI agents.

features

Key Features of ZizkaDB

ZizkaDB provides a suite of features designed for deep operational intelligence and debugging of AI agents in production environments. These capabilities enable teams to gain granular insight into agent decision-making and performance.

  • Replay (technology): End-to-end replay of agent sessions, including LLM calls, tool usage, and multi-agent interactions.
  • Trace (technology): Causal lineage (why()) that stores every agent step as a linked event to trace decisions.
  • Measure (technology): Behavioral drift alerts to detect when agent behavior deviates from an established baseline.
  • Operational (other): Operational data monitoring for production AI agents.
  • Catch (technology): Regression detection by comparing replayed sessions against baselines.
  • Time-Travel Debugging: Rewind agent runs with point-in-time precision to identify root causes.
  • Semantic History Search: Search agent history using natural language queries.
  • Dashboard Features: Activity, Behavior, Reports, Suggestions, and Fleet for cross-agent monitoring (managed cloud/enterprise).

use cases

Who Should Use ZizkaDB?

ZizkaDB is primarily designed for AI engineering teams and developers who are building, deploying, and maintaining AI agents in production. Its specialized features address the unique challenges of agent observability and debugging.

  • AI engineering teams: For faster debugging and resolution of issues in live AI agents.
  • Developers: To investigate agent behavior, including prompt changes, skipped tool policies, and inconsistent answers.
  • Teams deploying AI agents: To catch regressions before they impact users by replaying agent sessions and detecting behavioral drift.
  • Organizations requiring operational visibility: To improve the reliability and understanding of AI agent operations.

how to use

How to Use ZizkaDB

ZizkaDB can be integrated into AI agent workflows through its SDKs and API, or deployed as a self-hosted solution. Users can begin by instrumenting their agents to log events to ZizkaDB.

  • 1Integrate the Python SDK or TypeScript SDK into your AI agent application.
  • 2Utilize the REST API for integration with any language or custom tools.
  • 3Deploy the self-hosted version using Docker for on-premise control.
  • 4Send agent events, decisions, and session data to ZizkaDB.
  • 5Access the ZizkaDB dashboard (managed cloud/enterprise) to replay sessions, trace lineage, and monitor drift alerts.
  • 6Configure baselines for behavioral drift detection to receive alerts on deviations.

pricing

ZizkaDB Pricing & Plans

ZizkaDB offers a freemium model with both self-hosted and managed cloud options, catering to different operational needs and scales. A 1-month free trial is available for managed cloud plans.

  • Self-Hosted: Free forever under the AGPL-3.0 license, offering unlimited events and projects on user infrastructure.
  • Pro: €29 per month for managed cloud service, including 50,000 events per month and support for 2 projects.
  • Team: €69 per month for managed cloud service, including 100,000 events per month and support for 5 projects.
  • Enterprise: Annual License for private deployments, single-tenant VPC deployments, commercial licenses, and priority support.

Pros

  • +Offers a free, open-source self-hosted option with unlimited events.
  • +Provides unique causal lineage (why()) for tracing agent decisions.
  • +Enables end-to-end session replay for visual debugging of agent interactions.
  • +Includes behavioral drift alerts to proactively detect deviations from baselines.
  • +Framework-agnostic integration via SDKs and REST API.
  • +Supports both self-hosting (Docker) and managed cloud deployments.

Cons

  • Managed cloud plans have event limits (50,000 for Pro, 100,000 for Team).
  • Requires integration and instrumentation of AI agents to log data.
  • Specific API rate limits for managed cloud plans are not explicitly detailed beyond event counts.
  • May require more manual integration for specific agent frameworks compared to tightly integrated alternatives like LangSmith for LangChain.

Similar Tools

ZizkaDB vs Competitors

ZizkaDB positions itself as an operational intelligence database specifically for AI agents, differentiating from broader MLOps platforms and general tracing tools by focusing on causal lineage and behavioral drift detection.

1

Specifically designed for developing, debugging, and monitoring LLM applications and agents built with the LangChain framework.

LangSmith is tightly integrated with LangChain, making it an excellent choice for users already building agents within that ecosystem. ZizkaDB is more framework-agnostic, potentially offering broader compatibility but might require more manual integration for specific agent frameworks.

2
Phoenix (Arize AI)

An open-source library for LLM observability, allowing users to trace, evaluate, and debug LLM applications locally or in their own environment.

Phoenix provides the tools for self-hosted LLM observability and debugging, offering high flexibility and control over your data. ZizkaDB offers a more opinionated, managed service or self-hosted solution with pre-built features for agent-specific monitoring, potentially requiring less setup but offering less raw customization.

3

Focuses on LLM observability, cost tracking, caching, and rate limiting, providing a comprehensive API management layer for LLMs.

Helicone excels at managing and optimizing LLM API calls, offering insights into cost and performance. ZizkaDB focuses more on the internal behavior and operational intelligence of AI agents, including replay and lineage, which Helicone doesn't emphasize as much, instead focusing on LLM API management.

4

A comprehensive MLOps platform for experiment tracking, model versioning, and model monitoring, with specific features for LLM evaluation and observability.

W&B is a broader MLOps platform that can track and monitor various aspects of AI models and LLMs, including evaluation and performance. ZizkaDB is more specialized in the operational intelligence and debugging of AI agents, with a stronger focus on behavior replay and lineage specific to agent decision-making.

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