Compliance risks held back innovation. Engineers now use Claude Code to validate every PR for privacy and write tests 80% faster.
One of Europe's largest telemedicine providers connects 2.5 million patients across Switzerland and Germany, handling approximately 3,000 remote consultations daily during peak periods.
Development cycles became bottlenecks as the feature backlog grew and regulatory requirements evolved. Engineers faced pressure to accelerate...
“Our development cycles were becoming bottlenecks to healthcare innovation. We needed to deliver faster while ensuring our existing systems remained bulletproof.”
Telemedicine platform providing 24/7 medical consultations via phone and video.
Integrated Claude Code into Medgate's development workflows and tested it across four teams.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Medgate's Software development is part of this use case:
Related implementations across industries and use cases
Strict quality standards slowed cycles. Claude now executes the build-test-fix loop, doubling execution speed.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
Early AI broke code. Using agents, engineers shipped 15 compliant apps, cutting sales cycles from 90 days to 30.
Strict quality standards slowed cycles. Claude now executes the build-test-fix loop, doubling execution speed.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
Manual EHR reviews and false alarms overloaded clinicians. Now, AI delivers plain-language patient summaries and early-warning alerts.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.
Compliance risks held back innovation. Engineers now use Claude Code to validate every PR for privacy and write tests 80% faster.
One of Europe's largest telemedicine providers connects 2.5 million patients across Switzerland and Germany, handling approximately 3,000 remote consultations daily during peak periods.
Development cycles became bottlenecks as the feature backlog grew and regulatory requirements evolved. Engineers faced pressure to accelerate...
“Our development cycles were becoming bottlenecks to healthcare innovation. We needed to deliver faster while ensuring our existing systems remained bulletproof.”
Telemedicine platform providing 24/7 medical consultations via phone and video.
Integrated Claude Code into Medgate's development workflows and tested it across four teams.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Medgate's Software development is part of this use case:
Related implementations across industries and use cases
Strict quality standards slowed cycles. Claude now executes the build-test-fix loop, doubling execution speed.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
Early AI broke code. Using agents, engineers shipped 15 compliant apps, cutting sales cycles from 90 days to 30.
Strict quality standards slowed cycles. Claude now executes the build-test-fix loop, doubling execution speed.
Talent shortages held back delivery. Engineers now use AI to review code 90% faster and cut 24-hour tasks to one hour.
Manual EHR reviews and false alarms overloaded clinicians. Now, AI delivers plain-language patient summaries and early-warning alerts.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.