Context

As part of the evolution of AI projects within Forem, the Information Systems Department wishes to expand its service offering by integrating a vector and NoSQL database solution. The solution will be an Azure component.

The anticipated increase in workload (data volume, queries, new AI use cases) requires ensuring a scalable, high-performance solution optimized for high-volume use cases (AI, RAG, hybrid search, etc.).

Mission Objective

Assess, define, and provide operational recommendations to industrialize the use of a vector database in an AI context, ensuring:

• Performance and robustness
• Cost control
• Long-term maintainability

Scope of the Mission

The consultant will work on the following areas:

• Analysis of the current architecture and planned use cases.
• Identification of constraints and risks related to:
• Scalability (data volume, QPS, latency)
• Vector index management
• Data distribution
• Security risks
• Recommendations on:
• Architecture choices (modeling, partitioning, indexing, RAG, hybrid search)
• Best practices for industrialization
• Scalability and resilience strategies
• Cost control
• Clarification of the roles and responsibilities of the IT Department’s management (infrastructure, data, development) regarding the use and governance of related technologies
• Proposal for a monitoring and observability approach (performance, consumption, alerting)
• Identification of key operational considerations (operations, maintenance, scalability)
• Concise and actionable summary for the IT Department

Expected Deliverables

• Document with clear and prioritized recommendations
• Target architecture diagram to facilitate implementation
• Concrete, directly actionable recommendations for technical teams
• Oral presentation to stakeholders

Execution Modalities

Duration: Maximum 10 days, spread between mid-January and end of February, depending on stakeholder availability.

On-site presence required for:

• Initial scoping
• Meetings for feedback and presentation of recommendations

The rest of the mission can be carried out remotely.

The consultant may rely on internal teams (data scientists, architects, technical experts, etc.) to successfully complete the mission.