Boomi
Software development
Manual coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
- 40% engineering team adoption
- 20% of code generated via AI
- 20% engineering productivity increase
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 coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Fragmented tools slowed release cycles. Now, developers use an AI assistant for instant code reviews before QA, accelerating sprints.
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 coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Fragmented tools slowed release cycles. Now, developers use an AI assistant for instant code reviews before QA, accelerating sprints.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
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 coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Fragmented tools slowed release cycles. Now, developers use an AI assistant for instant code reviews before QA, accelerating sprints.
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 coding took 40% of dev time. With AI handling code generation and security scans, engineering productivity rose 20%.
Fragmented tools slowed release cycles. Now, developers use an AI assistant for instant code reviews before QA, accelerating sprints.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.