01
For one blocked model workflow
First release
Scope one modality mix, one dataset release, and the acceptance criteria that prove it is useful.
- Defined model objective
- Bounded data and workflow scope
- Dated success review
Pricing for Physical AI
Price the path from sensor data to model improvement.
Avala scopes the platform around the loop you need to run: modalities, data volume, quality, compute, deployment, and whether you need managed operations. Start with a bounded release; expand when the loop proves value.
Starting points
Start at the stage your model needs.
No generic seat ladder. Choose the smallest commercial path that can prove the next dataset release, then expand the same system.
02
For recurring model improvement
Production loop
Run ingest, curation, human + AI labeling, QC, versioning, and export as one repeatable system.
- Recurring dataset releases
- Quality evidence and lineage
- Model feedback and re-label
03
For multiple programs and teams
Enterprise control plane
Standardize how sensor data is governed, released, and connected to training across the organization.
- Deployment and security scope
- Integrations and access controls
- Optional managed operations
Cost drivers
The quote follows the work the model actually needs.
Every proposal names the assumptions behind the scope, so teams can see what is included and what changes as they scale.
01
Data
Modalities, scene volume, capture cadence, retention, and the dataset release you need to publish.
02
Workflow
The stages Avala runs, from ingest and curation through annotation, QC, export, and re-label.
03
Infrastructure
Compute, storage, integrations, deployment model, security requirements, and support level.
04
Operations
Whether your team operates Mission Control or Avala supplies collection, labeling, and QC capacity.
Commercial principles
Clear enough to underwrite.
Start bounded
Begin with one model objective, a defined dataset release, and written acceptance criteria.
See what drives cost
The scope names usage measures, included capacity, owners, and the changes that affect the quote.
Expand on evidence
Add modalities, programs, and operational capacity after the loop proves value.
Pricing questions
What teams ask before scoping.
Why isn't there one list price?
Physical AI programs vary by modality, volume, workflow, infrastructure, and operations. Avala turns those inputs into an explicit scope instead of hiding them behind an arbitrary seat tier.
Can we begin with one workflow?
Yes. The first-release path covers one model objective, a bounded dataset release, and agreed acceptance criteria before you expand.
Do we have to use Avala's managed operations?
No. Mission Control is the platform and system of record. You can add managed collection, labeling, and QC capacity when your team needs execution support.
What happens in the pricing session?
We map one sensor-to-model loop and its data, workflow, infrastructure, and operating assumptions. Then we define the inputs for a written scope and set a date for the next step.
Build the right first release
Bring the bottleneck. Leave with the scope.
We will map the smallest deployment that can move one model workflow forward and make every commercial assumption visible.