Fill the form and we’ll contact you soon

Your information has been received.
Looks like we're having trouble

Fill the form and we’ll contact you soon

Your information has been received.
Looks like we're having trouble

Case Study

Large Language Model Implementation

We’re not a regular consulting firm. More than Data & AI suppliers, we are reliable partners. Both transparency and independence are at the core of how we work and guide the development of strong and reliable partnerships with our clients.

Contact Us

Overview

The project's main objective was to develop a customized implementation of the GPT 4 Large Language Model for a Government Agency, with the purpose of creating an AI chatbot capable of providing information to Government officials and interacting with citizens to offer support and assistance. By creating this communication tool, the project aimed to improve efficiency and customer satisfaction while reducing the workload of the Agency.

Challenge

Incorporating contextual knowledge into GPT like models require a lot of fine-tuning and careful consideration of the type of knowledge that is being incorporated. Overall, successfully incorporating contextual knowledge into GPT-like models requires a balance between accuracy, efficiency, and relevance to the task.

Problem

Approach

We begin by ingesting contextual data in various formats such as PDFs, lists, and text files. This data is then passed through an embedding layer, which generates context for queries. Using this contextual information, we deploy a chatbot model capable of handling inquiries from citizens, leveraging the additional context provided by the embedding layer while limiting the scope to a specific domain.

Computer Vision

At DareData, we specialize in offering personalized AI solutions that incorporate the unique requirements of businesses. Our primary focus is on incorporating private context into GPT-like models, allowing companies to have their own version of ChatGPT-like tools. With the ability to retrain or utilize pre-generated context, we enable organizations to harness the power of AI while maintaining data privacy. Our goal is to provide you with AI solutions that empower your company to have personalized tools, tailored specifically to your needs.

Time Line

01

arrowelipse

Context Embedding

02

arrowelipse

Deployment of In-House ChatGPT Tool

03

arrowelipse

04

arrowelipse

arrowtimeline

Mar-Apr 2023

Apr -May 2023

Key Insights

Incorporating Contextual Knowledge: The project highlights the challenge of successfully incorporating contextual knowledge into GPT-like models. This process requires careful fine-tuning to strike a balance between accuracy, efficiency, and relevance to the task at hand.

Personalized AI Solutions: The project aims to provide customized AI solutions tailored to the specific needs of businesses. By enabling companies to have their own version of ChatGPT-like tools, organizations can leverage AI technology while maintaining data privacy and enhancing efficiency.