GenAI knowledge base performance strategy¶
Objective¶
Define a technical roadmap for improving the performance of knowledge base GenAI applications by adopting a data-driven approach evaluation and measurement.
Description¶
Reliability is key to the value proposition of RAG-based application products. However, these applications are often plagued in production by quality problems such as hallucinations and other sub-optimal responses. By adopting a data-driven approach to evaluation, observability and development priorities, technical teams can build reliable systems out of unreliable components.
With a decade of experience developing classic ML applications, and significant hands-on experience with GenAI applications in the last two years, Liam is a valuable advisor in addressing this long tail of necessary improvements for your GenAI knowledge base system. He takes a practical approach, defining a custom roadmap for your development team that prioritizes quick wins while laying the foundation for sophisticated domain-specific solutions.
The discussions will also cover the best practices and tools for knowledge system development that top teams have adopted to optimize development velocity and shorten iteration cycles. With code examples and detailed diagrams, I define a standard of excellence for this new type of system that results in a significant improvement in response quality that end users experience.
Engagement Details¶
Key Activities¶
Workshops: Through a series of discovery workshops, We'll review your current application, RAG approaches, evaluation systems and development processes. We'll describe best practices for the development team to adopt.
Design: Based on your input, we'll design additional system components, processes and logical application flows for improving your GenAI system performance.
Roadmap: Following our design collaboration, we'll summarize the current state of your GenAI application, identify the top priority features and initiatives to implement, and craft an implementation plan.
Deliverables¶
- GenAI knowledge base performance workshops
- Custom roadmap and implementation plan for improving your GenAI knowledge base performance
- Summary of best practices and tools applicable to your application All diagrams and documentation developed during the engagement including source code, scripts, templates, and other technical artifacts