Identity layer
Give every dataset a durable identity
Version sensor data, labels, schemas, permissions, and exports under one stable record teams can find, reproduce, and cite.
Physical AI model enablement
The model enablement layer for Physical AI
Turn raw sensor data into versioned, traceable training artifacts—and keep every production model connected to the data that shaped it.
Avala Cloud, your cloud, or on-premMCAP, LiDAR, video, image, audio, and text
Why Avala
Infrastructure for the data behind every Physical AI model
Avala gives Physical AI teams one operational system for transforming sensor data into governed model inputs—not a chain of disconnected labeling projects.
Operational control plane
Operate the full data-to-model loop
Coordinate ingest, visualization, human and AI labeling, quality control, publishing, training, drift, and re-labeling in one system.
Managed operations
Scale execution without fragmenting the stack
Add qualified people, automated workflows, and rigorous consensus when programs need throughput—while your data and lineage stay in the same control plane.
One continuous loop
From sensor capture to model improvement
Each stage writes back to the same governed record, so teams can move faster without losing context, quality, or provenance.
- 1Ingest
- 2Curate
- 3Label
- 4Quality control
- 5Publish
- 6Train
- 7Improve
Dataset Ops
Make your data work at scale
Manage massive sensor streams with built-in versioning, lineage tracking, and search—engineered for production workloads, not prototypes.
Connected to the same dataset record
Annotation Ops
Turn human expertise into production data
Route tasks, enforce labeling guidelines, and coordinate distributed teams with QA that's measurable—not subjective.
Connected to the same dataset record
Model Management
Understand model behavior
Monitor for drift, track real-world performance, and trace any prediction back to the training data that influenced it.
Connected to the same dataset record
Mission Control
See and control the work—not just the final delivery
Explore sensor data, design workflows, inspect quality, manage dataset versions, and trace model decisions from a single operating surface.
Data Management
Organize, Search & Share
Avala manages traceable dataset deliveries today and is building stable references, immutable revisions, sealed manifests, and rights metadata for repeatable training.
Annotation & Alignment
Label with Full Traceability
Turn synchronized camera, LiDAR, and telemetry into reviewed training data for Physical AI. Label in 2D, 3D, and across sequences without losing the context your models need.
Training & Deployment
Train, Host & Monitor
Manage experiment lineage, fork datasets for rapid iteration, and gate releases on automated benchmarks or human review. From training to hosting, Mission Control keeps every decision recorded for confident, auditable deployment.
Integrations
Connect your existing infrastructure
Connect your data, training, and deployment stack
Built for Physical AI
One enablement layer across embodiments and environments
Bring the same governed operating model to robotics, autonomous systems, field data collection, and critical infrastructure.
The business case
More model progress from every hour of captured data
Replace operational handoffs with compounding data assets that remain useful, reproducible, and ready for the next training cycle.
Preserve model context
Trace a model, benchmark, or production issue back to the exact dataset version, labels, and policies that shaped it.
Shorten iteration cycles
Move from data discovery to correction and re-training without rebuilding context across tools and vendors.
Govern deployment your way
Run in Avala Cloud, your cloud, or on-prem with permissions, retention, auditability, and enterprise controls built into the workflow.
Operations when you need them
Software control with managed execution
Avala can supply the operational capacity behind demanding programs. The people and automation scale up or down; the dataset identity and control plane remain yours.
Explore managed operationsOpen and programmable
Build with Avala
Python SDK, REST API, and CLI. Manage datasets, trigger annotations, and export results programmatically.
$ pip install avala
from avala import Client
client = Client()
dataset = client.datasets.get("dataset-uid")
Research & perspectives
What Physical AI teams are learning now
Technical analysis, field lessons, and practical guidance for building better data-to-model systems.
ResearchAug 10, 2026
Four bottlenecks, three workarounds: robot learning in 2026
Robot learning's strongest 2026 papers attack memory, reasoning, dexterity, and world modeling. Three of the four work around data the field cannot collect yet.
Read morePhysical AIAug 8, 2026
The data quality curve: what each data defect costs
Some defects wash out, some poison a policy at trace doses, and the worst hide behind healthy training loss. We map the curve, and set out to price it.
Read more
Robotics DataJul 9, 2026
What robot data costs, and where budgets leak
Cost per hour differs by orders of magnitude across the four layers of robot data, and it is the wrong metric. Four budget leaks to audit.
Read moreBuild the data foundation your models can compound on
Turn every sensor dataset into durable model progress
See how Avala can connect your data, operations, and production models in one enablement layer.