Generative AI Solution

The vendor is required to provide generative artificial intelligence (GAI) solution to enhance educational services across the division.
- GAI solution is to improve information access for students, families, and the community, personalize and improve student learning, support staff course scheduling, and streamline administrative decision-making through the secure and responsible use of artificial intelligence.
- A comprehensive, scalable, and flexible GAI solution through leveraging unique hcps data by incorporating GAI, retrieval-augmented generation (RAG), language models, or other related models and technologies, that can securely retrieve up-to-date information from internal or external sources in a controlled, k–12 appropriate manner.
- The proposed solution must deliver the following core services:
1. Assessment of hcps’ data, data governance, and infrastructure
•    Assessment of hcps’ current data architecture, privacy policies, and governance structure for readiness to implement a generative AI powered solution.
•    Identification and proposal of changes to data handling processes and specific data systems necessary for secure and effective deployment of the GAI solution.
•    Ensure compliance with FERPA, COPPA, CIPA, and other relevant student data privacy laws and previously stated hcps' AI guiding principles.
•    Verification of hcps infrastructure such that it’s fully integrated with successful offeror’s GAI solution.
2. Data management, security, and integration
•    The successful offeror must design secure data flows for the integration of the GAI solution across various hcps systems, data sets, and web content to include implementing safeguards such as auditing, reporting, encryption, data minimization, access control, and role-based access to endure full compliance with k-12 data privacy standards and common data governance policies.
•    Content moderation capabilities must be provided to ensure that outputs are user role and age appropriate and include documented logic to maintain the integrity of the solution. 
•    Tools to detect and mitigate risks such as bias in training data, model design and outputs, hallucinations, prompt injections, or misuse must be included.
•    The successful offeror shall collaborate with hcps stakeholders to define ongoing governance and oversight protocols, to ensure that the implementation and integration of the GAI solution are effectively managed and aligned with the division’s goals.
3. GAI solution design, development and quality assurance
•    The successful offeror will tailor the design solution using data specific to county and the hcps GAI five use cases (attachment j) defined in this request for proposal. thorough testing will follow, with each step of the process designed to guarantee accuracy and continual tuning, optimizing responses to align with the division and requirements.
•    The proposed GAI solution must be scalable and inclusive. 
•    The successful offeror shall ensure accessibility for all users, including compliance with the act (ADA). 
•    Every aspect of functionality and quality benchmarks referenced in will be met, creating a robust and reliable GAI solution ready to serve the educational needs of hcps.
4. GAI solution implementation plan, deployment and performance
•    the successful offeror’s implementation plan for the GAI solution should encompass a clearly defined timeline with distinct phases, outlining each critical milestone along the journey. 
•    It will designate specific roles and responsibilities to ensure smooth management and execution, adhering to performance requirements that guarantee the solution’s efficacy.
•    Data integration and data security will be meticulously planned to secure sensitive information and ensure compliance with established privacy standards. 
•    The technical environment hosting the GAI solution will be optimized for reliability and scalability, preparing for seamless deployment and robust operation. 
•    Post-launch, the plan must include comprehensive monitoring protocols to continuously oversee the performance and security of the implemented solution, ensuring it consistently meets the division's learning objectives and maintains the highest standards of trust and integrity. 
5. GAI solution maintenance and support 
•    Continual maintenance and support shall be provided for the GAI solution so that it performs optimally to meet expectations. 
•    Expectations of timing for scheduled events are clearly articulated and notice expectations for unplanned outages will be defined. 
6. Training and documentation 
•    As the implementation of the GAI solution is set in motion, a well-defined training plan for GAI solution usage will be shared. 
•    This plan will be designed to empower division administrators, staff, and technical teams with the knowledge required to effectively use, maintain, and govern the technology. 
•    In parallel, comprehensive technical documentation will be provided by the successful offeror, serving as a steadfast guide to support implementation, ongoing maintenance, and long-term sustainability. 
•    This documentation, rich in detailed instructions and best practices, will be an invaluable resource for ensuring the seamless integration and operation of the GAI solution. 
•    Recognizing the importance of ethical and safe use, the initiative will include student-facing resources. 
•    These materials should be thoughtfully crafted to educate and inspire students, encouraging responsible and informed engagement with AI technologies. 
•    The training and documentation efforts will form a robust foundation, ensuring the GAI solution will thrive within the educational landscape of hcps. 
•    The successful offeror partnering with a reputable professional development organization specialized in GAI to provide training and documentation to staff, as needed, is acceptable, to ensure successful adoption and optimization of GAI solution use within hcps.

- Contract Period/Term: 2 years
- A Pre-Proposal Conference Date: September 2, 2025
- Questions/Inquires Deadline: September 9, 2025