Interactive AI Chatbot Based on the GPT Model
Our client is one of the subsidiaries of the largest telecommunication holding in Japan, ranked 55th in the Fortune Global 500. The company provides one of Japan's largest internet access
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AI-Powered Linguistic Tool
This project involves the development of three critical solutions for a linguistic technology company. These include an intelligent question-answering system for automating responses, a smart scraping with advanced DOM analysis for accurate data extraction, and migration to LLaMa-2 to enhance data security and reduce third-party dependencies. These solutions improve efficiency, data security, and competitiveness.
Project background
The driving force behind this project is to harness the power of AI and advanced language models to address specific business challenges and opportunities. The project comprises three distinctive but interrelated initiatives:Question Answering System, universal smart scraping, and migration to Meta’s LLaMa-2.Each part is tailored to improve efficiency, enhance data security, and maintain a competitive edge in the linguistic technology sector.
At its core, this project signifies a proactive response to the changing demands of linguistic technology services, focusing on developing software for indexing documents, and a dedication to providing cutting-edge solutions that meet and exceed their clients’ expectations.
- Duration: April 2023 – Ongoing
- Location: The USA
- Industry: Linguistic technologies
- Services:
- AI & Machine Learning
Business needs
01
Automation and Optimization: The question answering system automates external requests and improves internal processes, reducing response times and boosting efficiency.
02
Data Extraction and Analysis: A smart scraping powered by Large Language Models extracts valuable information from websites, helping the client stay competitive and up-to-date.
03
Risk Mitigation: Migrating to Meta's LLaMa-2 from GPT-3.5 and GPT-4 minimizes risks associated with third-party applications, enhancing data safety and scalability.
04
Integration and Scalability: Microsoft Azure integration and Kubernetes usage ensure seamless cloud services and easy scalability.
05
Cross-Functional Collaboration: The involvement of linguists ensures linguistic accuracy in the Question Answering System.
06
Innovation and Modernization: The client adopts modern tools and practices, maintaining technological independence and future readiness.
Product features
– Generate the continuation of the input text
– Extract terminology from monolingual or bilingual input files
– Detect any mismatches between specific metrics in the source
– Use a document indexing system for filtering
– Tailor queries for precise responses from Q&A Bot
– Boost efficiency by handling multiple queries at once
– Protect sensitive data and gain autonomy
– Work with content in various languages
– Streamline processes and reduce manual effort
Solution
The driving force behind this project innovation, advanced AI capabilities, and practicality to address specific business challenges effectively. Here’s a breakdown of the provided solutions:
The Q&A System for Documentation-Based Queries:
We’ve created an intelligent Q&A bot that simplifies responses for both internal and external queries. This system incorporates a dynamic document indexer for swift filtering of extensive corpora, even within hierarchical structures, to extract contextually relevant information. Additionally, advanced prompt customization allows users to refine their queries by specifying the number of documents considered, ensuring precise and tailored responses, while multi-request processing enhances efficiency and responsiveness.
Universal Web-Scraper:
Our universal smart scraping is developed to extract crucial web content. It employs advanced DOM tree analysis, taking into account the hierarchical structure of web pages for precise data extraction. This approach enhances the accuracy of data extraction from various sources.
Migration to Meta’s LLaMa-2:
Facilitating the migration to Meta’s LLaMa-2 model enhances data security and reduces third-party dependencies. Key features include heightened data security, minimized risks associated with external services, and the ability to create custom APIs for tailored interactions and applications, fostering greater flexibility.
Our technology stack
- Python
- Qdrant Vector Database
- Langchain
- Microsoft Cognitive Tools
- Docker
- Kubernetes
- Terraform
- Flask
- React
- TypeScript
- Microsoft Azure
Key achievements delivered
01
Achieved a 20% boost in efficiency and responsiveness by implementing query responses automated workflow.
02
Enhanced data extraction capabilities with advanced analysis, resulting in a 15% improvement.
03
Significantly improved data security and architectural independence, achieving a 40% increase in the migration project.
04
Provided the capability to develop custom APIs for specific use cases.
05
Optimized the client's operations with an intelligent Q&A Bot and maintained current web content thanks to smart scraping.
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