A naukri.com initiative
Dropbox
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149
Image Credit: Dropbox
Building Dash: How RAG and AI agents help us meet the needs of businesses
- Dropbox Dash is a product designed to help knowledge workers organize, share, and secure content across various applications.
- The product utilizes AI-powered features like advanced search and content access control to improve productivity and collaboration.
- Developed using retrieval-augmented generation (RAG) and AI agents, Dash offers powerful search capabilities and granular access controls.
- Challenges in building the product included data diversity, data fragmentation, and data modalities unique to business environments.
- RAG, an industry-standard approach, was chosen for its ability to combine information retrieval with generative models for accurate responses.
- Choosing the right retrieval system and model was crucial for Dash, balancing latency, quality, and data freshness considerations.
- AI agents play a key role in handling multi-step tasks autonomously, breaking down complex queries into actionable steps.
- The agents follow a structured planning and execution process, leveraging LLMs and DSLs for efficient task handling.
- Lessons learned include the importance of selecting appropriate tools, optimizing prompts for different LLMs, and understanding trade-offs between model size, latency, and accuracy.
- Future directions include enabling AI agents for multi-turn conversations, self-evaluation, fine-tuning LLMs, supporting multiple languages, and fostering collaboration across diverse teams.
- Integrating RAG and AI agents has enhanced Dash's AI capabilities, aiming to meet businesses' needs and advance the future of knowledge work.
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