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Optimizing Generative AI Experimentation with Custom Solutions

Business Challenge

A large enterprise required AI-driven solutions to enhance experimentation and improve infrastructure efficiency. Existing tools lacked scalability and personalization.

Advisory Approach

The MultiModal Chatbot and Custom Use Case features of the Gen AI Lab were leveraged to create personalized LLM workflows. Workshops identified performance gaps, and iterative experiments explored various LLMs and embeddings. Recommendations included deploying modular configurations and leveraging the Gen AI Lab’s customizability features for user-specific optimizations.

Technologies & Frameworks:

Tools:
LangChain, LlamaIndex

Frameworks:
Agile-based iterative experimentation, RAG Studio

Capacities:
Multi-modal capabilities for adaptive user inputs

Business Outcomes

Scalability:
Improved resource utilization across environments.

Speed:
Accelerated experimentation timelines by 40%.

Accuracy:
Enhanced use-case-specific accuracy by 30%.

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