- AWS Advanced Tier Services Partner
- Established 1999
Software Development Case Studies
These software development case studies cover projects JBS Dev delivered in AI, cloud, data, and custom software. Each one names the problem, the systems involved, what we built, and the result.
WHAT THEY SHOW
What Our Case Studies Show
Each JBS Dev case study covers one delivered project: the client's problem, what we built, and the result.
The projects include agentic and generative AI, machine learning, cloud migration, legacy modernization, data platforms, and web and mobile applications. Many connect to systems the client already ran, such as FIS DataConnection at a regional bank or Epic medical records at a healthcare technology company.
Most run on AWS, with services such as Amazon Bedrock, AWS Lambda, and Amazon SageMaker. Some run on Microsoft Azure.
Named and anonymized clients
Some case studies name the client, such as Wine Access or Tidal Basin. Others describe the client by industry, such as a regional bank. Both report the same kind of project facts and results.
FEATURED
Featured Results
Three projects from three industries, with the numbers from their case studies.
30,000
Records a day, with no manual work
Financial Services
Automating 30,000 Daily Records for a Regional Bank
Challenge: Staff moved about 30,000 records a day from FIS DataConnection to ActiveCampaign by hand, after two to three years of failed automation attempts.
Result: An AWS Lambda and Python pipeline now runs the transfer daily with no manual work, delivered in just under four months.
Read the regional bank case study100+
Jobs moved to Azure in 213 days
Restaurants
Integration Platform Migration for a Top Worldwide Restaurant Chain
Challenge: A costly, unreliable proprietary workflow platform was nearing contract expiration.
Result: More than 100 jobs moved to VisualCron, SSIS, and .NET Azure APIs in 213 days, with estimated annual savings in the hundreds of thousands of dollars.
Read the restaurant chain case study85-90%
Forecast accuracy on Amazon SageMaker
Manufacturing
Generative AI Sales Forecasting for a Manufacturer
Challenge: Traditional statistical models couldn't forecast product-level demand accurately, causing both excess inventory and shortages.
Result: A generative AI time-series model on Amazon SageMaker consistently reached 85 to 90% forecast accuracy, outperforming earlier statistical and machine learning methods.
Read the manufacturer forecasting case study"JBS feels more like an extension of our internal team than a traditional vendor relationship."
Senior IT Leader, AmeriVet Partners
ALL CASE STUDIES
Browse All Case Studies
Here are 34 JBS Dev case studies, one card per delivered project. Each card links to the full case study.
Case study
Eliminating the Need to Manually Process 30,000 Records Per Day for a Large Regional Bank
See how JBS Dev and Starfish used AWS to eliminate manual processing of 30,000 daily records for a large regional bank.
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Case study
Transforming Healthcare Tech: Intelligent Document Processing with GenAI
How JBS Dev applied generative AI to extract and standardize medical record data for a healthcare technology company.
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Case study
Implementing a GenAI-Powered Knowledge Base with AWS
See how JBS Dev used AWS OpenSearch and large language models to help manufacturing teams find answers in technical documentation.
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Case study
AI-Driven Sales Forecasting on AWS for Manufacturing Inventory Optimization
How JBS Dev used AI and AWS to improve product demand forecasting and help a manufacturer manage inventory risk and cost.
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Case study
Modernizing Knowledge Management with Agentic AI on AWS
How JBS Dev modernized an industrial company's knowledge base with agentic AI on AWS, improving access to product documentation.
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Case study
Modernizing Real Estate Operations With Agentic AI
See how JBS Dev used AI and AWS to streamline MLS listing creation, reduce manual entry, and improve consistency for real estate teams.
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Case study
Migrating a Legacy Shipping Platform to AWS for Optimization
How JBS Dev modernized a bulk liquids shipping platform on AWS, improving reporting and adding a customer portal.
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Case study
Generative AI Solution for Efficient Knowledge Retrieval and Proposal Generation
How JBS Dev built an AWS-based generative AI solution to help engineering consultants search internal documents and create proposals.
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Case study
From Siloed Systems to Data Powerhouse
How JBS Dev connected a post-acute care provider's siloed systems through a centralized data warehouse for business intelligence.
Read case study
BY INDUSTRY
Case Studies by Industry
Each industry page shows its case studies next to the systems and problems common in that industry.
FAQ
Case Study FAQs
What do JBS Dev's software development case studies cover?
They cover projects JBS Dev delivered in agentic and generative AI, machine learning, cloud migration, legacy modernization, data platforms, systems integration, and web and mobile applications. Each one states the client's problem, the systems involved, what we built, and the result. Industries include manufacturing, healthcare, retail, financial services, logistics, real estate, automotive, and education.
Why don't some case studies name the client?
We name a client only with its approval. When a client isn't named, the case study describes it by industry and size, such as a regional bank or a top worldwide restaurant chain, and keeps the project facts the same. Every metric stays with the project it came from, including qualifiers such as "about" or "estimated."
How long did these projects take?
It varied with scope. The regional bank's daily records pipeline took just under four months. The restaurant chain's integration migration moved more than 100 jobs in 213 days. Petco's curbside pickup launched in under six weeks. For your project, an assessment sets the timeline before work starts.
Do you have a case study in my industry?
The case studies cover manufacturing, healthcare and life sciences, retail and QSR, financial services, logistics, real estate, automotive, and education, plus public sector and professional services work. If your industry isn't listed, most of the work still applies: modernizing applications, connecting systems, building data platforms, and adding AI with people reviewing its output.
