Draft a risk-mitigated Statement of Work document for machine-learning-based patent landscape analytics for an aerospace composites supplier, including secure data ingestion procedures, algorithm training assumptions, IP disclosure boundaries, and iterative feedback gates aligned with funding tranches

Generate draft a risk-mitigated statement of work document for machine-learning-based patent landscape analytics for an aerospace composites supplier, including secure data ingestion procedures, algorithm training assumptions, ip disclosure boundaries, and iterative feedback gates aligned with funding tranches for Other Professional, Scientific, and Technical Services industry

Other Professional, Scientific, and Technical Services

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Upload patent documents or patent landscape reports that will serve as the primary data source for ML training
Specify ITAR, EAR, or other government security requirements governing the patent data
Identify specific aerospace composite technologies for patent landscape analysis
Define iterative feedback gates tied to funding release schedules and ML model validation checkpoints
Specify what constitutes confidential versus public information in patent analytics outputs
Document key assumptions for ML model training including data quality, market assumptions, and technical constraints
Identify regulatory and certification requirements for the Statement of Work
Define stakeholder groups and their respective access rights to SOW deliverables
Select pre-approved risk mitigation approaches for aerospace ML analytics projects
Specify format and detail level for Statement of Work final delivery