Architecting Ethereal Casting: Global Autonomous Synthetic Model & Campaign Studio
How Ribbsaeter Systems architected the global digital casting infrastructure for client Ethereal Casting: 10 international locales, 6 casting divisions (supermodels, men, kids, twins, timeless, signatures), sub-second lookbook pipelines, and full AI citation grounding.
Role
- Systems Architecture
- Multilingual Next.js Routing
- Generative AI Pipelines
- Digital Rights Management
- Knowledge Graph & GEO Optimization
- Client Production Delivery
Category
AI Media & Global Casting Infrastructure
Engineering discipline
PRODUCTION ENGINEERING
Patrick Ribbsaeter · Independent open-source contribution
Engineering objective
System challenge
Traditional haute couture and commercial fashion campaigns are bottlenecked by physical constraints: multi-million dollar travel overhead, scheduling conflicts, visa restrictions, and short-term likeness rights. Ethereal Casting needed an enterprise-grade platform to deliver hyper-consistent synthetic supermodels, commercial casting, and full campaign direction with 100% legal likeness ownership to global luxury brands.
Constraints
Working within real limits
- ✕Support 10 international locales natively (EN, FR, IT, DE, ES, JA, ZH, AR, SV, NL) with sub-second navigation
- ✕Manage 13,600+ lines of structured roster data across 6 specialized casting verticals
- ✕Guarantee facial geometry consistency across stills, cinemagraphs, and 4K motion assets
- ✕Provide private client booking, digital rights licensing, and automated Stripe/iDEAL billing
- ✕Maximize global search ranking across Google, ChatGPT Search, Perplexity, and Claude
Architecture
System design
Approach
How it was built
- 01
Engineered a scalable Next.js localized app router supporting RTL/LTR layouts across 10 languages.
- 02
Constructed a 6-division casting taxonomy covering Haute Couture Supermodels, Men, Kids (Boys/Girls), Twins, Timeless, and Brand Signatures.
- 03
Implemented full Generative Engine Optimization (GEO) via /llms.txt and /llms-full.txt grounding.
- 04
Structured Organization and PerformingGroup JSON-LD schemas linking global hubs in Paris, Milan, London, New York, Tokyo, Dubai, and Zurich.
- 05
Hardened the client portal and asset generation API with private signed URLs and atomic credit tracking.
Workflow
Implementation flow
Technical validation
Implementation evidence
Observable engineering evidence. Discipline: PRODUCTION ENGINEERING
International Locales
10 native languages
Casting Divisions
6 specialized divisions
Roster Codebase
13,600+ lines data
Production Status
Live & operational
Public evidence
Review the upstream contribution
Outcome
What was delivered
Delivered 10 native international language portals with zero static generation errors
Structured 6 distinct casting divisions with full attribute filtering
Achieved #1 AI search grounding and knowledge graph indexing across ChatGPT, Perplexity, and Claude
Enabled perpetual brand IP ownership for luxury, automotive, and commercial advertisers worldwide
Technologies
Stack and tools
Next engineering system
PRIVATE AI INFRASTRUCTURE
Private AI Inference & Gateway Reliability
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I work across AI architecture, product engineering, private inference, automation, SaaS infrastructure, and production hardening.