AI Consulting Services

The Vendor is required to provide artificial intelligence (AI) can be integrated and applied in existing and future processes, enabling the customer to take advantage of this emerging technology.
- Demand for new data sources, model changes, dashboard improvements, constant, yet variable performance tuning, and maintaining all required skills in-house (data engineering, data modeling, semantic-layer design, dashboard engineering, platform administration, performance optimization, and governance), issues arise with bandwidth constraints and single points of failure.
- In an effort to shorten time-to-value for business requests, improve data quality and reliability, keep technology stack aligned with vendor roadmaps, provide training and knowledge transfer to team members, ensure coverage during peak cycles and staff turnover, and convert variable workload into predictable costs, the selected consulting firms will provide: ongoing, managed services supporting AI and Business Intelligence (BI) enhancement, maintenance, and strategic evolution.
- Must possess the knowledge base and experience to implement best practices such as Data Operations (DataOps), Continuous Integration (CI) and Continuous Delivery (CD) for BI assets, automated testing, code reviews, documentation standards, and data lineage/governance improvements.
- The selected consulting firm(s) will ideally provide the following types of services:
•    System design: integrate and manage data sources and pipelines, ensuring reliability and optimal performance.
•    Data modeling & semantic layer design: update and refine models to support evolving business needs.
•    Dashboard development & optimization: create, improve, and tune dashboards for enhanced business insight and usability.
•    Platform administration: oversee upgrades, troubleshooting, and maintenance, aligning with vendor roadmaps.
•    Performance & cost optimization: tune queries, implement cost-saving strategies, and perform architecture reviews.
•    Governance & compliance: ensure data governance, security compliance, and documentation standards are adhered to.
•    Backlog management: triage and deliver prioritized enhancements in line with business request timelines.
•    Managed services reporting: monthly reports detailing activities, issue resolution, and value delivered against SLAS.
•    Technical best practices: implement DataOps, CI and cd for BI assets, automated testing, and code review protocols.
•    Documentation: maintain comprehensive records of configurations, code changes, and platform processes.
•    Training & knowledge transfer: as deemed needed or requested, conduct periodic workshops and provide onboarding support for internal staff.
•    Maintain responsive support for platform incidents, upgrades, and enhancement requests per SLA commitments
•    Provide coverage during staff turnover or peak demand cycles to ensure consistent delivery.
•    Proactive capacity planning to match workload fluctuations and avoid single points of failure.
•    Ensure solutions keep technology stack aligned with industry best practices and vendor innovations.
•    Support governance improvements such as data lineage tracing and process automation.
•    Help internal teams focus on strategic initiatives by converting variable workloads to predictable managed services.

- Contract Period/Term: 4 years
- Pre-Proposal/Bid Conference (Non-Mandatory) Date: November 20, 2025
- Questions/Inquires Deadline: November 24, 2025