Avala vs Rerun
Rerun is an open-source multimodal data visualization SDK — one slice of the data infrastructure stack. Avala is Physical AI Infrastructure-as-a-Service — the whole stack: ingest, fuse, reconstruct in 4D, auto-label with customer-trained models, human-verify, version, train, deploy, monitor. Closed-loop, end to end.
Feature Comparison
Avala | Rerun | |
|---|---|---|
| Platform Type | Model enablement layer connecting sensor ingest, visualization, labeling, QC, dataset releases, training, and feedback workflows | Open-source multimodal data visualization SDK |
| Data Types Supported | Sensor-native workflows for synchronized camera, LiDAR, radar, video, and supporting telemetry | Broad visualization support — 2D, 3D, time-series, and multi-modal logging |
| Annotation Capabilities | Human and AI labeling across 2D, 3D, and temporal sensor workflows with configurable quality control | Programmatic annotation context for visualization (labels, colors, keypoints) — not a data labeling tool |
| Workforce / Human-in-the-Loop | Optional managed operations connected to the same dataset records and quality workflows | N/A — Rerun is a developer SDK, not a data labeling platform |
| Security & Compliance | Data boundaries, access controls, retention, and deployment requirements scoped with each program | Self-hosted (open-source) — full control over data |
| Deployment Options | Avala Cloud, customer cloud, or on-premises, scoped to program requirements | Local/self-hosted open-source SDK |
| Physical AI Specialization | Purpose-built for the Physical AI data-to-model loop, from sensor ingest through drift and re-labeling | Development-time visualization — no production data infrastructure or annotation capabilities |
| Pricing Model | Scoped to data, workflow, infrastructure, and optional operations requirements | Open-source core, commercial plans for team features |
Key Differentiators
Production infrastructure vs developer tool
Rerun is a development-time SDK for logging and visualizing multimodal data with programmatic annotation overlays. Avala is where that data goes next — production annotation pipelines, managed workforce labeling, and enterprise deployment for model training.
Annotation + workforce built in
Rerun helps you see your data. Avala helps you label it at scale with 15,000+ trained annotators, native 4D annotation tooling, and quality assurance workflows designed for Physical AI ground truth.
Enterprise-grade data operations
Rerun focuses on the developer experience. Avala provides enterprise data ops — versioned datasets, compliance workflows, air-gapped deployments, and end-to-end lineage tracking from raw sensor data to trained models.
Why teams choose Avala
Teams choose Avala when they need to move from development-time visualization to production data infrastructure. Rerun lets you explore data during development; Avala operationalizes that data into annotated, curated, production-ready datasets for Physical AI.
Ready to see the difference?
Book a demo and we'll map how Avala connects your sensor data, quality operations, dataset releases, and production models.
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