AI Hub Consulting Service

The Vendor is required to provide for consulting services to support the design, development, and launch of the data commons collaborative (DCC), a foundational initiative under the state AI Hub.
- This engagement aims to centralize access to data for AI development, research, and innovation.
- evaluated based on their proposed architecture design, approach to metadata management, security and governance frameworks, ability to support synthetic data generation, and AI fairness capabilities.
- The Data Commons Collaborative (DCC) aims to:
•    Aggregate and host curated datasets
•    Enable synthetic data generation
•    Ensure ethical, fair, and secure AI development
•    Provide an extensible platform for researchers, government, startups, and industry.
- Program Management and Coordination
•    Develop and maintain an integrated project plan and timeline
•    Conduct regular meetings and stakeholder updates
•    Ensure milestones defined in the DCC project plan are met
- Technical Architecture and Platform Development
•    Design and build the data commons website and backend infrastructure
•    Implement metadata management, cataloging, and discovery tools (e.g., CKAN, Dataverse)
•    Develop role-based access and identity management system
•    Develop a central ledger for tracking “Commons Credits”
•    Enable API-based data access and usage analytics
- Dataset Curation and Integration
•    Assist in curating the initial set of datasets
•    Ensure metadata completeness and FAIR data principles
•    Support ingestion pipelines, version control, and provenance tagging
- Synthetic Data Capability
•    Integrate synthetic data tools (e.g., SDV, Synthea, CARLA)
•    Support synthetic dataset generation and validation pipelines
•    Ensure compliance with privacy and audit policies
- AI Fairness and Bias Framework
•    Implement bias detection, auditing, and mitigation tools (e.g., AIF360, Fair learn)
•    Establish bias impact documentation workflows and dashboards
- Security, Governance and Compliance
•    Define and implement RBAC, MFA, and dataset tiering
•    Ensure logging, encryption, and audit trails
•    Define terms of use and enforce ethical data handling
- Testing, Rollout, and Adoption
•    Conduct QA across platform functions
•    Train end users and administrators
•    Prepare documentation and support materials
•    Support public launch.

- Questions/Inquires Deadline: September 02, 2025