Prasad Venkatachar | AI Solutions Engineering Director
VAST Data

Future of Memory and Storage - Day 2 @ 08:50

Blueprint for Domain Adoption of LLMs Using Post Training and Agentic RAG

Enterprises are rapidly experimenting with large language models (LLMs), yet many domain initiatives stall between proof-of-concept and reliable production deployment. The primary blockers are not model capability alone, but domain specificity, factual grounding, controllability, evaluation rigor, and operational governance—especially in regulated or high-stakes environments. This talk presents an end-to-end, tested blueprint for domain adoption of LLMs by combining three complementary pillars: (1) prompt engineering for rapid task alignment and controllable behavior, (2) parameter-efficient fine-tuning to encode domain style and reasoning patterns, and (3) agentic Retrieval-Augmented Generation (RAG) to ensure grounded, traceable answers at scale.

Prasad Venkatachar, AI Solutions Engineering Director, VAST Data

×

Prasad Venkatachar / Blueprint for Domain Adoption of LLMs Using Post Training and Agentic RAG

Prasad Venkatachar, AI Solutions Engineering Director,
VAST Data

He is working as AI Solutions Director at VAST Data.  He has 20 years of progressive experience in Solution architecture, Product Strategy & Management, Marketing and IT Services.

Close