Each Angular upgrade consumed months of manual testing. Agentic AI finds and fixes breaking changes, freeing engineers for clinical work.
A healthcare technology provider whose EHR and care coordination platforms support over 165 million community-based care patients, with product lines spanning millions of lines of Angular code across behavioral health, post-acute care, and e-prescribing.
Each Angular upgrade cycle required months of planning and manual regression testing to confirm that changes hadn't broken clinical software...
“The question was always, 'How do we get to our target version of Angular, and what does the plan look like?' AWS Transform helped to simplify the process by automatically detecting the breaking changes and applying broad modifications across large, complex code bases. That story repeats from team to team, which is exactly why you want a repeatable system like AWS Transform.”
EHR software and services for healthcare and human services organizations.
Cloud computing platform and on-demand infrastructure services.
Netsmart's Code modernization is part of this use case:
Related implementations across industries and use cases
Manual upgrades bottlenecked the roadmap. AI agents now handle the refactoring, letting engineers run large-scale updates in parallel.
Manual coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
Manual upgrades bottlenecked the roadmap. AI agents now handle the refactoring, letting engineers run large-scale updates in parallel.
Manual coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Each Angular upgrade consumed months of manual testing. Agentic AI finds and fixes breaking changes, freeing engineers for clinical work.
A healthcare technology provider whose EHR and care coordination platforms support over 165 million community-based care patients, with product lines spanning millions of lines of Angular code across behavioral health, post-acute care, and e-prescribing.
Each Angular upgrade cycle required months of planning and manual regression testing to confirm that changes hadn't broken clinical software...
“The question was always, 'How do we get to our target version of Angular, and what does the plan look like?' AWS Transform helped to simplify the process by automatically detecting the breaking changes and applying broad modifications across large, complex code bases. That story repeats from team to team, which is exactly why you want a repeatable system like AWS Transform.”
EHR software and services for healthcare and human services organizations.
Cloud computing platform and on-demand infrastructure services.
Netsmart's Code modernization is part of this use case:
Related implementations across industries and use cases
Manual upgrades bottlenecked the roadmap. AI agents now handle the refactoring, letting engineers run large-scale updates in parallel.
Manual coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
Manual upgrades bottlenecked the roadmap. AI agents now handle the refactoring, letting engineers run large-scale updates in parallel.
Manual coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.