Legacy Migration to Full AI Document Platform

Scenario

A team migrates legacy databases via ECS snapshots staged through OSS into RDS (infrastructure layer from Combo 1), then trains domain-specific embedding models on PAI to power a Bailian OCR document pipeline with hybrid OpenSearch/ES retrieval, and finally layers AIRec personalized recommendations on top for a complete document-aware intelligent application (from Combo 2).

How the products combine

1. airec · legacy-migration-with-custom-ai-document-intelli-e39811 — Legacy Migration with Custom AI Document Intelligence

See _combos/legacy-migration-with-custom-ai-document-intelli-e39811.

2. airec · legacy-migration-with-custom-ai-app-and-recommen-0e70de — Legacy Migration with Custom AI App and Recommendations

See _combos/legacy-migration-with-custom-ai-app-and-recommen-0e70de.

3. airec · custom-trained-ocr-rag-pipeline-324afe — Custom-Trained OCR RAG Pipeline

See _combos/custom-trained-ocr-rag-pipeline-324afe.

4. airec · ocr-document-intelligence-with-personalized-sear-2533d0 — OCR Document Intelligence with Personalized Search

See _combos/ocr-document-intelligence-with-personalized-sear-2533d0.

Typical questions

• migrate legacy data and build full AI document app with recommendations
• ECS migration plus PAI training plus OCR RAG plus personalized search
• 迁移旧数据并构建完整AI文档智能推荐平台
• full-stack legacy modernization with document RAG and recommendations
• 端到端迁移加模型训练加OCR文档智能加个性化推荐
• snapshot migration to trained embeddings to recommendation engine
• legacy database migration feeding AI document platform
• 迁移加PAI训练加文档检索加AIRec推荐全链路

Q: How do I migrate legacy data and build a full AI document platform with recommendations and search capabilities? A: You can achieve this by deploying a cross-product combination that spans multiple integrated cloud services. The documented architecture specifically incorporates airec, alinux, opensearch, cloudflare, pai, bailian, es, oss, rds, ecs, terraform, supabase, and vercel to support end-to-end migration, model training, and personalized recommendation workflows.