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Data Analysis & Query Generation

Data Analysis & Query Generation 

AI-powered platform to automate data analysis and deliver actionable insights through real-time conversational queries.  

  • Country  Germany 
  • Service    Data Analytics and Artificial Intelligence
  • Industry  Multiple




Process Followed

  After lining up salient details related to inventory management and logistics application development, our team outlined a course of action that would be followed to develop a comprehensive solution. The process comprised of identification of problems, considering the relevant factors of the solution, taking note of common challenges faced, and coming up with the outcome in the end.


Problem Identification 

Feasibility study 

Solution Implementation 

Challenges 

Final Outcome 

Client Overview

Client Overview

Our client, based in Germany, was seeking advanced business solutions to streamline their operations and enhance productivity. They approached QSS with a vision to redefine data analysis and query generation, aiming to empower businesses with a comprehensive platform integrating data analysis, model creation, and interactive data conversations. 

Feasibility Study

The client identified a critical challenge faced by companies overwhelmed with large volumes of data, struggling to efficiently extract actionable insights. They explored the feasibility of developing an AI-powered platform capable of quickly analyzing diverse data sets and generating solutions to complex business problems.

  • Assessing AI models like LangChain and Llama 2 for processing CSV and PDF data formats and delivering real-time query responses.
  • Evaluating the integration of real-time conversation features and personalized recommendations within a user-friendly interface for non-technical users.
  • Ensuring the system can scale to handle increasing data volumes efficiently using FAISS vector stores and AWS cloud infrastructure.
  • Estimating the business impact of automating data analysis to speed decision-making, reduce reliance on data experts, and democratize data access.

Feasibility Study

Solution Implementation

Data Analysis & Query Generation was successful because of smart moves and new tech, despite challenges. Efficient management of structured and unstructured data was achieved by integrating LangChain, Zep, and Pinecone for end-to-end vector storage and indexing. The addition of the Large Language Model ensured scalability and performance. User research and usability testing sessions led to iterative design refinements, resulting in a groundbreaking platform that democratizes data analysis and provides actionable insights. 


Product discovery workshop

Our Product Discovery Workshop is a collaborative, structured session designed to align stakeholders, understand user needs, and define clear project goals. Through workshops involving brainstorming, user journey mapping, and feature prioritization, we help clients uncover key product requirements, validate ideas, and identify technical feasibility early on. This process minimizes risks, accelerates development timelines, and ensures the final solution delivers maximum value to users and the business.


Product discovery workshop

Competitor Analysis

A thorough Competitor Analysis enables us to understand the market landscape, identify strengths and weaknesses of similar products, and uncover opportunities for differentiation. By examining competitors’ features, user experiences, pricing models, and technology stacks, we provide actionable insights that inform product strategy and positioning. This competitive intelligence helps our clients build solutions that stand out, address unmet needs, and gain a strategic advantage in their industry.

Key Features

Key Features

  • Automatic Data Analysis : Automatically analyzes structured and unstructured data to deliver quick insights.
  • Target Variable Selection : Allows users to select a target variable from CSVs for focused data analysis.
  • Linear Model Integration : Enables linear regression analysis for simplified data interpretation.
  • Recommendation Engine : AI suggests solutions to business problems, supporting smarter decisions.
  • Interactive Data Conversations : Lets users interact with data via natural, real-time queries.
  • Persistent Chat Query Storage : Stores user queries using Zep and Pinecone for faster, context-aware responses.

Challenges

The Challenges

  • To develop algorithms capable of parsing both structured (CSV) and unstructured (PDF) data formats.  
  • To develop algorithms to automatically perform linear regression analysis on the uploaded data.  
  • To implement recommendation engines capable of analyzing data patterns and providing actionable insights.  
  • To integrate natural language processing (NLP) models to facilitate interactive conversations between users and their data.  

Final Outcome

  • Data Analysis & Query Generation aims to democratize the realm of data analysis, making it more inclusive and accessible to a diverse range of users.  
  • The platform offers seamless functionality, allowing users to effortlessly upload their data sets, conduct in-depth analyses, and obtain customized recommendations tailored to their specific needs.   
  • It enables users to engage in dynamic, real-time interactions with their data sets, facilitating the instant generation of insights and actionable information.   
  • By providing intuitive tools and features, it empowers users to streamline their decision-making processes.  
  • It serves as a bridge between raw data and actionable insights, facilitating the transformation of data into valuable knowledge that can drive informed decision-making and strategic planning.  


Final Outcome

Information Architecture​

Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation
Data Analysis & Query Generation

Technology Stack  

AWS AWS Glue
Node.jsTypeScript
Pyhton ​ Python ​
ReactJS React JS ​
Web3.js   Stream lit
Scikit-learn Scikit-learn
XG Boost XG Boost
Pandas   Pandas
Numpy Numpy  
FastAPI FastAPI
Postgres    Postgres   
Cohere Cohere
Google Gemini     Google Gemini
OpenAI Chat GPT-4 OpenAI Chat GPT-4  
Zep  Zep 
Pinecone Pinecone

Project Consultation with an expert

  • Grasp your development needs.
  • Illuminate our process for pairing you with qualified, thoroughly vetted developers from QSS Technosoft Inc.
  • Discuss the subsequent steps, frequently resulting in finding the perfect match within less than one day.
Book Consultation

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Call us at +1 (612) 201-1169

For Job write us at career@qsstechnosoft.com