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Rerun

Multimodal data stack for logging, visualizing, and querying physical AI data.

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About

Rerun is building what it calls the data layer for Physical AI: infrastructure for logging, visualizing, querying, and training on multimodal sensor data from robots, drones, and autonomous vehicles. Its open-core model pairs the Rerun SDK (Apache-2.0/MIT) for visualization and data logging with the commercial Rerun Hub for team-scale cataloging, transformation, and GPU-direct training pipelines.

Founded in Stockholm in 2022 by ex-Volumental teammates Nikolaus West, Emil Ernerfeldt (creator of the egui GUI library), and Moritz Schiebold, the company raised a 15.6 million euro seed round in March 2025 led by Costanoa Ventures with Seedcamp participating, following a 3.2 million euro pre-seed. Its open-source visualizer is used in projects at Meta, Google, Hugging Face's LeRobot, and Unitree.

Caveats: the commercial Hub is still maturing, and the product is purpose-built for physical-AI workloads rather than general ML observability, so fit depends on working with sensor and 3D data.

What it can do

  • Multimodal data logging SDK
  • High-performance 3D and video visualizer
  • Time-aware data queries
  • Rerun Hub team data platform
  • ROS and robotics ecosystem integrations

Setup

pip install rerun-sdk or add the Rust crate; log data with the SDK and view in the Rerun viewer.

Prerequisites

Python or Rust environment; sensor or 3D data streams to log.

Use cases

data-visualizationroboticsmultimodal-datadebugging

Works with

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 82; Trending score 78/100 from researcher assessment.

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.