Reducing Errors & Manual Interaction in Document Management Using ML/NLP
Reducing Errors & Manual Effort in Document Processing Using Vision and NLP The Challenge A real-estate technology firm had implemented a less efficient, semi-automated process to match and map data from a multitude of inspection reports with various formats, to an estimate for works needed. This process was time-consuming, error prone and expensive. Tatras was […]
Content Transformation using Deep Learning
Content Transformation using Deep Learning The Challenge Making tutorial videos are difficult and time consuming. Moreover as the speaker speaks only in one language it is hard to reach a larger audience due to lack of multilanguage version. Tatras was tasked by a leading EdTech company to create a solution that will transform the tutorial […]
Autograding Speech assessments in Language Learning using Deep Learning and LLMs
Autograding Speech Assessments using Deep Learning and LLMs The Challenge A leading publisher of language content needed a solution for auto-grading speech assessments against a given topic based on several factors like pronunciation accuracy, tone of voice, relevancy to the given topic etc. The existing cloud solution does not provide all of these and not […]
Vintage Curve Analysis for Credit Risk using Natural Language Queries using LLMs
Vintage Curve Analysis for Credit Risk using Natural Language Queries using LLMs The Challenge A financial institution wanted to build a question-answering system capable of responding to natural language queries. This system would leverage bank loan dataset to generate responses and was to draw the Vintage Curve for given queries. Tatras used an open-source large […]
Cross Selling Products using LLM driven Machine Learning
Cross Selling Products using LLM driven Machine Learning The Challenge A financial company wanted to develop a Customer Targeting system for campaigns like attrition, upselling, and cross-selling services such as credit cards. Tatras developed a solution that leverages AutoML and GenAI capabilities, where users simply upload customer’s past data on transactions, investments, banking, etc., and […]
Fraud Investigation using LLMs and Graph Databases
Fraud Investigation using LLMs and Graph Databases The Challenge A company aims to develop a question answering system for fraud investigators to detect factors leading to fraudulent transactions from fraud data. The challenge lies in transactions possibly sharing relationships among them. To address this, Tatras developed a solution using network graphs and GenAI, significantly enhancing […]
Identify potential Money Laundering from transaction history using Graph Databases and LLMs
Identify potential Money Laundering from transaction history using Graph Databases and LLMs The Challenge A financial institution aims to build a system to detect money laundering patterns and unusual transactions. The challenge lies in the complexity of the problem, which goes beyond a straightforward ML-based approach. Analyzing factors such as past transactions and transaction recipients […]
Customer Segmentation based Customized Product Recommendation using Unsupervised Learning and LLMs
Customer Segmentation based Customized Product Recommendation using Unsupervised Learning and LLMs The Challenge A financial institution aimed to group customers based on diverse characteristics such as demographics, behaviors, hobbies etc. The goal was to identify various customer segments to understand their unique traits. To address this challenge, Tatras was tasked with creating a solution using […]
Document Vetting for Credit Risk using Open Source LLMs
Document Vetting for Credit Risk using Open Source LLMs The Challenge A financial institution faced challenges with a cumbersome and costly process to validate bank statements for loans and credit. This included checks for monthly transactions, a three-month transaction history, recent activity, and meeting specified minimum account balance requirements. Tatras created a GenAI based streamlined […]
Root Cause Analysis for deviation in fault rate in high precision Manufacturing
Root Cause Analysis for deviation in fault rate in high precision Manufacturing The Challenge Our client, a global leader in data storage solutions, had a problem in their manufacturing unit. They were experiencing high variance in failure rate of disks produced, from one day to the next. This caused losses due to scrapping as well […]