Visualize, debug, and analyze your spatial and embodied AI data—effortlessly.
Based on user reviews
Rating Distribution
Harvey Riggs
3 months ago
Tried Rerun for a month with a robotics dataset. The Python SDK handled 3D data smoothly, and real-time visualization sped up debugging. Still, setup and advanced queries took time. Worth it, but not super beginner-friendly.
Albert Schaper(Artificial Intelligence, AI Tools)
Rerun earns a 4.0/5 rating from 1 user review, with Albert Schaper recommending it for Data Analytics use cases. Albert Schaper's background in artificial intelligence makes this recommendation especially relevant for software developers seeking artificial intelligence tools.
Pricing: starts at $0 / month(Updated November 2025)
Free open source SDK; commercial managed data platform for teams is available via contact, pricing not public.
Usage Model: Projects, Pay-as-You-Go — ensuring you only pay for what you actually use.
Rerun's free tier makes it an attractive option for software developers looking to experiment with data analytics tools. The free plan includes core features sufficient for personal use and small-scale projects. For software developers needing enterprise-grade capabilities, the paid plans offer expanded functionality, better performance, and dedicated support.
Rerun is an open-source data platform for visualizing, logging, and analyzing multimodal data such as images, point clouds, text, and 3D scenes. It is designed for applications in robotics, spatial and embodied AI, simulation, and computer vision, providing SDKs, a flexible visualizer, and query tools to help users understand and improve complex, sensor-driven systems.
Understanding the core functionality and approach of Rerun.
Usage-based pricing keeps Rerun aligned with actual consumption. Finance teams pay only for the outcomes the organization really uses. Usage-based billing keeps costs aligned with real adoption.
Explore the powerful features that make Rerun stand out.
Official SDKs handle authentication, retries, and error handling automatically.
Teams can inspect the codebase and adapt Rerun to specific environments.
Trigger-based flows keep work moving without extra check-ins. Automation handles the repetitive work so teams can focus on strategy.
Dashboards and analytics surface the metrics teams need to act. Analytics and reporting surface the metrics needed to act quickly.
Discover how different audiences leverage Rerun for their specific needs.
Generate unit tests, documentation, and API clients automatically from existing code. Automation handles the repetitive work so teams can focus on strategy.
Product teams lean on Rerun to test features, gather feedback, and prioritize roadmaps using real data. Analytics and reporting surface the metrics needed to act quickly.
Operations teams rely on Rerun to orchestrate tasks across departments. Automation handles the repetitive work so teams can focus on strategy.
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Use this page as a starting point to evaluate Rerun alongside similar options. Our directory focuses on practical details that matter for adoption—capabilities, pricing signals, integrations, and real audiences—so you can shortlist with confidence and move from exploration to evaluation faster.
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Before adopting any tool, model your total cost at expected usage, verify integration coverage and API quality, and review privacy, security, and compliance. A short pilot on a real workflow will reveal reliability and fit quickly. Bookmark this site to track updates to Rerun and the broader ecosystem over time.
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