Launching Q1 2026

The Data Platform for Physical AI

Scalable infrastructure that understands robotics data natively

OUR MISSION

Build the data platform every robotics team needs

Why This Matters

Robotics teams waste most of their time on data infrastructure. Every robot generates gigabytes of sensor data per minute, all streaming simultaneously. Teams string together storage solutions that break at scale, write custom pipelines that need constant maintenance, and watch their best engineers debug infrastructure instead of teaching robots new behaviors.

How We Build

We're building from first principles for robotics data. That means native understanding of temporal alignment, coordinate frames, and sensor fusion. Our platform handles the complete data lifecycle: ingestion from heterogeneous sensors, distributed processing at fleet scale, and direct integration with training pipelines. The same infrastructure that today requires dedicated teams will just work out of the box.

Our Vision

When data infrastructure stops being a bottleneck, the entire field accelerates. Instead of every company rebuilding the same infrastructure, they focus on making robots actually useful. Small teams can tackle problems that currently need entire departments. Physical AI is at an inflection point. The companies that win will be the ones with the best models and algorithms, not the biggest infrastructure teams.

THE PROBLEM

The data infrastructure gap

Robotics teams waste months building data infrastructure that should already exist. Unlike web or mobile development, robotics has no standard data stack. Every team rebuilds the same complex pipelines from scratch.

No Industry Standard

Teams build custom data pipelines from scratch, spending months reinventing the same solutions imperfectly.

Fragmented Representations

Data is represented differently in robot logs, storage systems, and training pipelines, requiring custom translation code.

Scale Complexity

What works for small datasets breaks at scale. Robots generate terabytes of multi-modal data daily, overwhelming custom-built infrastructure.

Slowing Innovation

Without proper versioning and traceability, teams spend time debugging pipelines instead of analyzing robot behavior.

OUR SOLUTION

Robotics-native data infrastructure

A complete data pipeline from robot sensors to training-ready datasets, handling collection, processing, and retrieval with robotics semantics preserved throughout.

STAGE 1

Data Collection

Onboard daemon captures multi-modal sensor streams with robotics-aware buffering, synchronized timestamps, and network-resilient cloud upload.

Time-synchronized multi-modal capture
Smart buffering & compression
Network-resilient upload
STAGE 2

Cloud Processing

Express complex robotics data transformations in simple, declarative pipelines. Use built-in operations that understand your data semantically or add your own code.

Accelerated processing, local or cloud
Built-in robotics operations
Run automatically on new data
STAGE 3

Data Retrieval

Query and stream your data with robotics semantics preserved. Filter by spatial relationships, find similar trajectories, explore synchronized multi-modal sequences.

Vector similarity search
Visualization integration
High-throughput training data serving
USE CASES

Complete robotics development lifecycle

Our platform serves every stage from data collection to production deployment.

THE TEAM

Alejandro Daniel Noel

Cofounder

Ex-Google engineer

Cristian Meo

Cofounder

PhD Generative AI

Join the future of robotics infrastructure

We're launching in Q1 2026. Sign up to get early access and help shape the platform that will power the next generation of physical AI systems.

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