Normalized claim
Ruby code migrated: 100,000 lines increase
In just eight weeks, Nextory migrated 100,000 lines of Ruby code
GCPEvidence: Medium50/100
Nextory modernizes media processing with agentic AI on Google Cloud
Use case typeSoftware modernizationUpdated Jul 7, 2026
Nextory worked with Google Cloud to map, analyze, and modernize its media processing system using agentic AI. The streaming platform used Google Cloud tools to reverse-engineer legacy Ruby code, prototype replacement architectures, and rebuild ingestion so it could handle large publishing back catalogs more quickly and scalably.
- Organization
- Nextory
- Industry
- Tech & Comms
- Location
- Sweden
- Published
- July 2026
Reported outcomes
100,000 lines
Ruby code migratedTime & speed
−87.5%rebuild time reduced−97.5%large-file processing time−83.3%publisher onboarding time250 instancesparallel processing instances
Strategic outcomes
Innovation & cultureAccelerated modernization with a repeatable agentic development patternScale & capacityEnabled parallel media processing and removed hard-coded dependenciesSpeed & agilityMaintained or improved quality while speeding up migration
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Rebuild time reduced: 87.5% decrease
In just eight weeks, Nextory migrated 100,000 lines of Ruby code, a project estimated at around six or seven months.
Normalized claim
Large-file processing time: 97.5% decrease
Large-file media processing now takes around two minutes rather than 80
Normalized claim
Publisher onboarding time: 83.3% decrease
publisher onboarding, previously measured in months, now takes about a week
Normalized claim
Parallel processing instances: 250 instances increase
Nextory can now spin up 250 processing instances and run each chapter in parallel
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Nextory
- Provider
- GCP
- Maturity
- Unknown
- Linked source
- Google Cloud Customer Story
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 3 of 3
- 1Software modernization
- 2Workflow orchestration
- 3Content processing automation
- Nextory's legacy Ruby on Rails media processing system struggled to keep up as new publishing agreements brought back catalogs of hundreds of thousands of titles.
- The rebuild was estimated at up to two developer years, and Ruby expertise was becoming increasingly hard to source.
- Nextory and Google Cloud engineers used Gemini CLI and Google Antigravity to reverse-engineer the existing codebase, generate technical artifacts, and test new architecture options.
- They selected an event-driven design using Java, Python, Pub/Sub, Workflows, and Cloud Run, with Google Kubernetes Engine also evaluated during the modernization effort.
- Nextory migrated 100,000 lines of Ruby code in eight weeks instead of an estimated six or seven months.
- Large-file media processing now takes around two minutes instead of 80, and publisher onboarding now takes about a week instead of months.
Architecture
Nextory used Gemini CLI and Google Antigravity to reverse-engineer legacy Ruby code, then co-engineered an event-driven architecture using Java, Python, Pub/Sub, Workflows, and Cloud Run for scalable parallel media processing.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jul 7, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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