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Altisource

Generate AI-driven modernization of Java legacy applications
AWS Real estate technology Enterprise deployment ⚙ Technical reference Deep case | Key delivery chain is substantially documented Evidence level A Production-grade R&D transformation
A Evidence level
Altisource boosts developer productivity with Amazon Q Developer
Publisher: AWS · Case of the official customer of the manufacturer · Direct sources at the case level
Claim origin: AWS and Client Disclosure · Independent verification: No · Accessed: 2026-09-19
Evidence level measures whether a source can be located and reviewed; it does not mean vendor-reported claims were independently audited.
Deep case | Key delivery chain is substantially documented 12 / 12
Business context2 / 2
Transformation workflow2 / 2
Technical workflow2 / 2
Human roles & governance2 / 2
Measured outcomes2 / 2
Source traceability2 / 2
All six dimensions meet the current completeness threshold.
The Altisource case placed the code Agent in a complete research and development closed loop containing project management, code warehouse, testing and secure scanning, and validated the modification using 350,000 line codes and four real applications.
Business problem

Altisource needs to re-engineer its business applications for more than 10 years to support new real estate and mortgage operations, but the legacy of Java has a large code volume and its context spread across Jira, Bitbucket and design documents, and the traditional re-engineering speed is difficult to meet the business window.

Solution

The company incorporated the generative AI into the enterprise-level modernization method, allowing Amazon Q Developmenter to re-configure, interpret and change recommendations in combination with the entire code library and Jira, Bitbucket and the design context; the team continued to use Scrum, testing, secure scanning and business demonstration to control delivery and validate effects with story points, gaps and application delivery.

Technical architecture & production workflow
Step 01
Legacy of Java code, Jira, Bitbucket and design file
→
Step 02
Enterprise-level context index
→
Step 03
Amazon Q Developmenter Understanding and Generating
→
Step 04
Reconstructing, testing and porosity scan of water flow lines
→
Step 05
Project Review and Business Demonstration Receiving and Inspection
→
Step 06
Story points, delivery cycles and measures of security outcomes
Key technology & infrastructure components
Amazon Q DeveloperJava Code LibraryJiraBitbucketCI/CD and testingSecurity Scan
Human roles & accountability

AI is responsible for understanding the legacy context, generating and re-engineering codes; engineers review design and codes, running tests and safety checks, and product and business owners take receipt and inspection functions and decide to publish them.

FDE delivery actions
  • Accessing tools to complete development context instead of individual document completion
  • Selecting legacy modernization as a clear operational objective
  • Maintenance of Scrum, Review, testing and safe access
  • Authentication with real application instead of sample code
  • Simultaneous measurement of changes in speed, output and gaps
Reusable delivery patterns
  • The code Agent value comes from the context of the warehouse and the project
  • Productivity indicators must be listed alongside quality and safety indicators
  • To demonstrate the state of modernization of applications
  • AI generation code cannot bypass existing engineering doors.
Business outcomes & delivery results

The AWS case revealed that team modernization exceeded 350,000 lines of Java code, with a 25 per cent increase in development productivity, four new applications delivered in four months and a 54 per cent reduction in code holes; the three-month average of Scrum story points went from about 160 to 200.

Evidence boundaries & verification notes
  • 350,000 lines, 25 per cent, 4 applications, 54 per cent were from AWS client cases.
  • The story point is not suitable for direct cross-team comparisons and can serve only as a clue to the changes that take place before and after the team.
Primary source: Altisource boosts developer productivity with Amazon Q Developer ↗
Traceable does not mean independently audited
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