Page 29 - D:\Book For College\Book 2 html5\

ALUMNI CORNER

MUNISH DHAL
MCA 2000-03
AIVION | Empowering Businesses with Affordable AI Solutions
AIVION Limited
Wokingham, England, United Kingdom

Smart Data Drives Smarter LLM Projects

When you're building LLM-based solutions, it’s not just about picking the right model — it’s also
about how you handle the data. Properly storing data, using vectorization effectively, choosing the
right database, and writing clear prompts are all key to making sure your model works well.
One of the biggest challenges with LLMs is that they sometimes fall back on their built-in knowledge
instead of using the specific data you’ve provided, like your company documents. To avoid this, you
need to create better prompts and set up ways to check if the answers they generate are actually
using the right data. Before the response goes to the user, you’ll want to verify it for accuracy. Plus,
organizing and summarizing your data can speed things up and help the model stay on track.

The most important thing to focus on is ensuring the LLM’s answers are spot-on. To do this, there are
two key things to check:
Relevance – Does the answer match what was asked?
Groundedness – Is the answer based on the data you provided?

Focusing on these elements ensures your LLM project is accurate, efficient, and truly helpful.

Reliable AI Insights, Powered by Your Data

The diagram above shows how data is stored and retrieved using a vector database. The top part explains
how different types of data are collected, while the bottom part shows how stored data is used to generate
and verify LLM responses.

MM Institute of Computer Technology & Business Management
https://www.mmumullana.org/ 25 CONTINUED...