Trust Center & Compliance
Environmental Sustainability Policy
Purpose
Establishes WEBSPACEAI's commitments to measuring and reducing the environmental footprint of training and inference at scale, elevating environmental disclosure from a Model Card footnote to a standalone governance commitment.
Scope
All training and inference compute across WEBSPACEAI Cloud and Project Zero.
Definitions
- Compute Footprint — estimated energy consumption and associated carbon emissions attributable to a training run or a defined volume of inference.
Policy Statements
WEBSPACEAI measures and discloses per-model training compute footprint in each Model Card Doc. 30 and aggregate inference footprint in the annual Transparency Report Doc. 29. WEBSPACEAI prioritizes efficient model architectures and renewable-energy-sourced compute where commercially available, and sets a directional goal of year-over-year improvement in energy-per-inference-token efficiency.
Responsibilities
WEBSPACEAI Cloud infrastructure team owns measurement methodology; Research owns architecture-efficiency roadmap; Policy Counsel reviews disclosure accuracy.
Compliance Requirements
Measurement methodology is published and available on request; disclosures align with emerging regulatory expectations on AI environmental reporting.
Enforcement
Inaccurate disclosures are corrected publicly upon discovery.
Reporting Process
Exceptions Process
Not applicable; disclosure is mandatory for qualifying training runs.
Review Process
Annual.