Rackspace Technology offers a pragmatic and collaborative approach to ascertain the practicality of AI within your distinct corporate context. Our method is rooted in agility, fostering a dynamic, iterative process that not only demonstrates the capacity to engineer an AI solution but also co-creates it, hand-in-hand with your team.

FAIR Generative AI Incubate meticulously constructs your MVP on AWS through a sequence of deliberate steps. We begin by pinpointing the optimal use case that aligns with Amazon Q capabilities, laying down a solid foundation for your AI endeavor. Subsequently, we establish the cloud infrastructure, ensuring a robust and scalable platform is in place.

Data sits at the core of any AI system, and we dedicate focused efforts to connect and prepare your datasets, readying them for insightful analysis and model training. The deployment phase sees the configuration and implementation of Amazon Q, transforming your raw data into intelligent, predictive insights.

Deliverables:

• Evaluate key data source
• Technology architecture
• Fine-tuning approach & requirements
• Prompt templates and definitions
• Assess data pipelines
• Amazon Q that is tuned for a specific task
• Prompt tuning
• Prompts, temperature and model P and K values to produce desired results
• Prompt engineering and training to improve performance against a specific task
• UI that makes it easy to interact with the inference
• Identify gaps to close before industrializing AI use