DegreeMe (ASU Online)
ASU Online’s degree catalog relied on manual upkeep, producing duplicate and stale listings that eroded recommendation trust; legacy serverless APIs struggled with long AI request times and inconsistent manual deploys; and config-driven forms created keyboard-focus and mobile-rendering failures.
Key metrics
- 143,999
- Degree search users
- 8,826
- Qualified conversions
- 92,730
- Organic search clicks
- 80.1
- Customer satisfaction (CSAT) score
Main features
What the platform does
AI recommendations
Turns multi-step quiz answers into tailored queries, returning the top 5 degree matches with AI-generated explanations.
Career path visibility
Surfaces institutional career pathways, matching titles and metrics synced live from DegreeMe's GraphQL endpoint.
Integrated RFI flows
Lets prospective students instantly request info from results cards with program-specific routing and secure API transfers.
How it played out
Challenges, approach and results
Intelligent & resilient matching
Matching students to the right ASU Online programs takes more than search — results must be relevant, explainable, and resilient when steps fail.
ECS migration & CI/CD pipelines
Ported legacy APIs to NestJS on AWS ECS, with secure automated deployment via Bitbucket Pipelines, ECR, and CloudFront S3 caches.
Accelerated deployments
Containerized AWS ECS enabled rapid, automated rollouts with manual gates for production stability.
Stale academic catalog syncs
ASU's degree catalog relied on manual upkeep, producing duplicate and stale listings that eroded recommendation trust.
Automated knowledge pipeline
Secured GraphQL sync pipeline fetches updated offerings, clears stale indexes, and runs structured batch-uploads on demand.
Elevated relevance
LLMs paired with Cohere reranking and modernized prompting sharply boosted recommendation precision.
Complex UI state & accessibility
Config-driven forms with Matter.js layouts created structural traps, causing keyboard-focus and mobile rendering failures.
Resilient AI recommendation pipeline
Modern pipeline using OpenSearch Vector Search, Cohere Rerank 3.5, and GPT-4o-mini, with strict fallbacks and Zod format parsing.
Optimized UI flow
Cleared focus traps, fixed responsive anomalies, and added offline error fallbacks for a polished onboarding path.
Tech stack
- Vue.js
- Nuxt 3
- TypeScript
- Matter JS
- GSAP
- Google Tag Manager
- AWS
Platform overview
Inside the finished platform
Impact
DegreeMe now provides an enterprise-ready, high-availability platform built to serve future generations of students. Migrating to NestJS on AWS ECS eliminated systemic timeout faults and drastically reduced query delays, while a secured GraphQL-based catalog sync pipeline now guarantees accurate, on-demand program data. The result is a lightning-fast, accessible, and personalized degree-selection experience with clear career path mapping — resilient advising, delivered at scale.
The engagement
What happened, in order
- Client or institution
- DegreeMe (ASU Online)
- Problem
- ASU Online’s degree catalog relied on manual upkeep, producing duplicate and stale listings that eroded recommendation trust; legacy serverless APIs struggled with long AI request times and inconsistent manual deploys; and config-driven forms created keyboard-focus and mobile-rendering failures.
- Project scope
- Built an AI-based degree recommendation engine that turns multi-step quiz answers into tailored queries, returning the top 5 degree matches with AI-generated explanations (OpenSearch Vector Search, Cohere Rerank 3.5, GPT-4o-mini, with strict fallbacks and Zod format parsing); migrated legacy APIs to NestJS on AWS ECS with automated Bitbucket Pipelines/ECR/CloudFront deployment; built a secured GraphQL sync pipeline for the academic catalog; and fixed accessibility and responsive-UI issues.
- Verified results
- 143,999 total degree-search users, 8,826 qualified conversions (RFI + app starts), 92,730 organic search clicks, and an 80.1 customer satisfaction (CSAT) score.
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Capabilities used in this work
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