The Missing Infrastructure Layer
The Data Platform
for Physical AI
Unified infrastructure for autonomous driving, robotics, and embodied intelligence. Ingest, compress, query, curate, and stream multi-modal sensor data at petabyte scale.
AI data infrastructure wasn't built for the physical world
The market has split into two camps—neither serves physical AI.
Vector Databases
Milvus, Weaviate, Qdrant, Pinecone—optimized for text-centric RAG workloads. No support for synchronized multi-sensor streams or spatiotemporal queries.
Columnar Formats
Lance, Vortex—great for analytics and compression, but treat multi-modal sensor data as opaque blobs. No per-modality compression, no scene semantics.
The result: Every major AV and robotics company builds proprietary data infrastructure from scratch. Petabytes per fleet per month, with no commercial product handling the full lifecycle.
Built from the ground up for multi-modal sensor data
Four fundamental design decisions that set Modalink apart from text-era data infrastructure.
The scene is the atom, not the row
Our storage format treats a scene — a time-windowed, multi-sensor recording with calibration, ego-pose, and annotations — as the fundamental unit.
- Scene-level versioning
- Scene-level semantic search
- Scene-level lineage tracking
Modality-native compression
Adaptive per-modality compression instead of generic encodings. Filters push down through compressed data without decompression.
- Octree + I/P-frame for LiDAR
- Temporal delta for IMU/GPS
- S3 → NVMe → GPU zero-copy
Built-in data curation
Semantic deduplication, automatic quality scoring, and per-sample lineage tracking run as storage-layer primitives — not bolted-on tools.
- MinHash + SemDeDup deduplication
- Sensor failure detection
- Per-sample lineage tracking
Edge-to-cloud lifecycle
From on-vehicle selective recording to depot bulk ingest to cloud-scale curation and training — a single platform spans the entire data journey.
- Novelty-based upload prioritization
- Petabyte-scale scene search
- Enterprise governance
Built for the teams no one else serves
Three underserved personas that existing tools ignore.
AV Data Curators
“Manually watching drive logs to find edge cases”
Find all unprotected left turns in rain at night — instantly. No more scrubbing through hours of drive recordings.
We give them Natural language scene search
Robotics Researchers
“Drowning in multi-TB datasets in fragmented formats”
One platform ingests every sensor format. Stream synchronized multi-sensor batches directly to your training loop.
We give them Universal ingest & efficient streaming
Perception ML Engineers
“Maintaining brittle pipelines between tools”
Stop gluing together annotation tools, data lakes, and training frameworks. One platform from raw sensor data to GPU-ready batches.
We give them A unified platform