About Spr

Growing companies know the right technology implementation is a balancing act: Address users’ expectations today while planning for tomorrow’s business demands. As a technology modernization firm, SPR helps companies strike that balance. We specialize in custom software development, cloud, data, and user experience solutions, working alongside companies to develop or modernize their digital products and platforms. Integrating our experts with our clients’ staff, we work collaboratively and provide proactive, pragmatic advice. We work alongside 150+ mid to enterprise-size clients across industries like professional services and manufacturing.

SPR has been named one of Crain’s Largest Private Companies in Chicago and is on the Built in Chicago Top 100 List of Digital Tech Companies in Chicago.

Locations

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Headquarter
  • Location

    233 S Wacker Drive Suite 3500 Chicago Illinois United States 60606

  • Location

    312-756-1760

Focus Area

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Spr's Technical Expertise

Java 13%
Javascript 13%
C# 12%
Python 13%
Ajax 12%
.NET 13%
Ruby on Rails 12%
GoLang 12%

Focus Client

  • Small Business (<$100000) 12%
  • Medium Business ($100001 - $500000) 46%
  • Large Business (>$500000) 42%

Spr's Industry Expertise

  • Information Technology 37%
  • Business Services 15%
  • Retail 14%
  • Financial & Payments 13%
  • Other Industries 13%
  • Manufacturing 8%

Portfolio

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Transforming Insurance Risk Management with Machine Learning

VGM Insurance wanted to streamline processes and enhance decision-making in claim applications using machine learning (ML). VGM faced challenges including fast-tracking ML projects amidst high failure rates, handling numerous application versions across multiple formats, and operationalizing predictive models. ? To gain insights from historical application and claims data, SPR: ? Implemented a flexible project approach to quickly adapt and refine solutions.? Achieved rapid team alignment, significantly reducing project time.? Used Microsoft Azure’s Document Intelligence Studio for OCR to extract data from application formats, including images and PDFs.? Developed a classification model to filter out non-application data, reducing unnecessary cloud costs.? Created and trained a highly accurate predictive ML model that significantly improved the client's ability to assess claim risk. ? Conducted ongoing experimentation to refine models and explore additional use cases for the data.? Achieved faster processing times, reduced costs, and enhanced decision-making capabilities.? Read More

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Industry

Information Technology

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Budget

Not Disclosed

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Timeline

23 weeks

Transforming Insurance Risk Management with Machine Learning

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