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A Secure LLM for Enhanced Information Sharing

Azati successfully developed a secure, locally hosted alternative to ChatGPT to improve corporate communication while maintaining strict confidentiality of organizational data.

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All Technologies Used

vLLM
vLLM
Open WebUI
Open WebUI

Motivation

The project aimed to create a corporate-ready ChatGPT alternative using open-source language models. The solution enhanced communication efficiency, ensured robust data security, and met modern corporate needs for information sharing and processing.

Main Challenges

Challenge 1
High Computational Resource Demands

Developing and running language models locally required substantial computational power, presenting challenges for resource-limited corporate environments.

Challenge 2
Identifying Optimal Models

Choosing an open-source LLM that provided quality on par with OpenAI’s GPT while catering to corporate communication required extensive research and testing.

Challenge 3
Ensuring Corporate Data Security

Protecting sensitive data during information exchange necessitated robust encryption, access controls, and secure integration mechanisms.

Key Features

  • Independent Local Deployment: Installed and configured models on internal servers for complete control over data processing.
  • Customized Corporate Integration: Seamless integration with organizational databases, tailored to specific data structures and workflows.
  • Enhanced Query Handling: Optimized response generation and query management with advanced RAG techniques.
  • Employee Training and Onboarding: Comprehensive training sessions to ensure effective adoption and usage of the new system.

Our Approach

Selection of Open-Source LLMs
Evaluated models like BERT and GPT-2, ultimately deploying Mixtral 8x7B and Mistral 7B for their suitability and performance.
Fine-Tuning with LoRA
Adapted the base models to the corporate domain through LoRA fine-tuning, ensuring relevance and accuracy in a business environment.
Model Quantization
Optimized the models to reduce memory usage, enabling efficient operation within constrained computational resources.
Enhanced RAG Techniques
Improved query response and content generation capabilities with features like parent query retrieval, multi-querying, keyword extraction, and HyDE techniques.
Data Security Protocols
Implemented advanced encryption and access controls, ensuring secure processing and storage of corporate data.

Project Impact

Azati’s solution replaced ChatGPT with a secure, efficient, and locally hosted alternative. The deployment enhanced communication within the organization, ensured strict data confidentiality, and reduced reliance on external cloud-based solutions. Local model deployment provided flexibility and superior performance, offering a scalable and secure framework tailored to the organization’s needs.

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