Clearly Define Your Business Objectives

A prominent US-based data aggregator aimed to speed up
information retrieval from their datasets and provide users with
the ability to visualize this data through a user-friendly interface.

Their objective was to utilize Large Language Models to process
extensive structured data volumes, replacing conventional
querying methods, and thereby delivering quicker and more
precise insights to their users.

Acquire & Synthesize Relevant Data

We pre-processed and transformed their knowledge repository comprising
of multi-relational databases. We leveraged vector databases to store this
information and selected the most appropriate retrieval mechanisms to
provide an effective solution.

Develop an Action Plan

Our methodology included experimenting, and benchmarking with different LLM architectures. Achieving the most effective solution involved multiple iterations, parameter tuning, and refinement based on continuous human feedback.

We created a query engine, designed to process structured data
and respond to user queries through simple natural language
commands.

This engine enables users to pose queries, ask follow-up
questions, and retrieve answers, which can then be visualized in
their preferred format.

Partner with You to See it Through

We developed a web application with an intuitive, user- friendly
interface that allows users to access the domain expert

The solution was deployed on the client’s preferred cloud
platform, ensuring flexibility and alignment with the client’s
choices.

We guarantee comprehensive documentation, training, and post-deployment support to ensure a smooth and successful implementation process.