CASE STUDY
NLP-Based Solution for Managing Data Similarities for an Information Services Provider
Industry | Information Provider
Technology | MLOps
Location | UK
The client is a professional information services provider using technology and expertise to provide insights and help businesses make informed decisions for growth, efficiency, and performance.
The team consists of more than 5,000 experts, including data experts, subject matter experts, and consultants who offer actionable intelligence across many industries including financial services, insurance, retail, automotive, etc.
Industry | Information Provider
Technology | MLOps
Location | UK
The client is a professional information services provider using technology and expertise to provide insights and help businesses make informed decisions for growth, efficiency, and performance.
The team consists of more than 5,000 experts, including data experts, subject matter experts, and consultants who offer actionable intelligence across many industries including financial services, insurance, retail, automotive, etc.
Challenges
How We Did It
Key Outcomes
90%
Semantic similarity score reached
85%
Accurate match in shorter transaction files (less than 50 terms)
70%
Accurate match in longer transaction files (more than 150 terms)
It was a great learning experience working with an industry-leading client in the information services sector. We started by understanding the client’s pain points and how the frequent influx of customers and their transaction files affected their business. The case allowed our data science personnel to create an MLOps-driven solution that would help them match their data similarities and locate inconsistencies promptly.
90%
Semantic similarity score reached
Audience
Case Study
Learn how our NLP-based solution helped an information services provider manage data similarities, increase Semantic similarity scores, etc.
