Design AI Powered Search System | Elasticsearch + Vector DB + System Design

In this video, we design a COMPLETE AI Powered Search System used by companies like Amazon, Google & Netflix.

We cover both:
✅ Traditional Search (Elasticsearch)
✅ AI Search (Semantic / Vector-based)

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🚀 What you’ll learn:

🔹 How Search Systems Work (End-to-End)
🔹 Elasticsearch Architecture (Shards, Replicas, Indexing)
🔹 Inverted Index Explained with Examples
🔹 BM25 Ranking Algorithm (Simple Explanation)
🔹 Near Real-Time (NRT) Indexing
🔹 Keyword vs Semantic Search
🔹 Vector Databases (FAISS, Pinecone)
🔹 Cosine Similarity vs Dot Product
🔹 ANN (Approximate Nearest Neighbor)
🔹 Hybrid Search (Best of Both Worlds)
🔹 Kafka-based Data Ingestion Pipeline
🔹 Caching (Redis) & Performance Optimization
🔹 Real-world Scaling (100M+ documents)

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🧠 Perfect for:
✔ System Design Interviews
✔ Backend Engineers
✔ 2+ to 15+ years experience
✔ FAANG / Product-based companies

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💡 Real-world examples included:
👉 Amazon search
👉 Google search
👉 YouTube recommendations

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📌 Topics Covered:
Search API design
Ranking algorithms (BM25)
AI embeddings
Vector search
Distributed systems
Scalability & fault tolerance

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#SystemDesign #AISearch #Elasticsearch #VectorDB #BackendEngineering

Видео Design AI Powered Search System | Elasticsearch + Vector DB + System Design канала Learning With Chetna