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What is rrweb?

rrweb is an open-source session replay and session recording library for capturing, replaying, and analyzing web user sessions. It is designed to serve as the replay infrastructure behind observability platforms, analytics tools, bug reporting products, automation systems, demo platforms, and custom developer products. rrweb records the fully rendered DOM and session event stream so teams can replay what users saw and did after JavaScript, dynamic content, and network-driven interface changes occur. Engineering teams can attach replays to error reports to understand the sequence of user actions, UI states, and context that led to a failure. Product and analytics teams can use rrweb to study clicks, scrolls, hesitation, navigation patterns, and real user journeys. QA and bug reporting teams can capture exact interaction sequences so developers can reproduce problems more easily. Automation teams can use rrweb’s structured capture of the rendered page as a reliable snapshot of what the user actually experienced. Demo platforms can use replay data to create reproducible product walkthroughs that can be embedded and updated without traditional video editing. rrweb Cloud adds managed hosting, scalable storage, indexing, querying, insights, deduplication, PII filtering, analysis, and processing for teams that do not want to operate the full infrastructure themselves. rrweb also supports AI workflows by exporting recordings as structured event streams that LLMs can summarize, triage, or consume through tool calls. By combining open-source session replay, extensible recording and playback, managed cloud infrastructure, privacy controls, and AI-ready event streams, rrweb helps teams build products that understand user behavior with far more context.

What is ZizkaDB?

ZizkaDB by Zizka AI is an operational database and intelligence layer built for teams running AI agents in production. The platform helps teams understand why an agent did what it did by capturing agent decisions, causal lineage, replayable sessions, behavioral baselines, and drift alerts. ZizkaDB is designed for situations where production agents change behavior after prompt tweaks, skip tool policies, answer the same question differently, or produce failures that ordinary logs cannot explain. With ZizkaDB, teams can replay a full session, inspect the decision trail, identify the exact source of behavior change, and confirm when a baseline has been restored. The platform supports event logging from Python, TypeScript, MCP, and REST, with one API key per agent and no heavy infrastructure project required. Teams can run ZizkaDB as an open source AGPL stack with Docker Compose or use the managed cloud version. The self-hosted version includes Activity, Behavior, Reports, and Suggestions, while managed cloud adds Fleet ranking across agents and projects. ZizkaDB also supports semantic search on history, time travel, cross-agent fleet queries, and checksum-backed events for tamper-evident decision history. Enterprise options include single-tenant VPC deployment, up to 50 agents, a Fleet dashboard, integration workshops, and dedicated support. The platform positions itself between traces, memory systems, and vector databases by focusing specifically on agent decisions, lineage, behavioral drift, and operational debugging. By combining production replay, causal lineage, drift alerts, behavioral reporting, self-hosting, managed cloud, SDKs, MCP support, and enterprise deployment, ZizkaDB helps AI teams stop debugging agents in the dark.