Rhea Kapoor

Rhea Kapoor

Aug 7

Vector Databases Under the Hood: Practical Insights from Automotive Data Implementation

2 min read

Rhea Kapoor

Aug 4

Why Our Vector Search Broke at 2M Queries/Day—And What Fixed It

3 min read

Rhea Kapoor

Jul 28

I Discovered What Matters When Scaling Workflow Automation

3 min read

Rhea Kapoor

Jul 25

My Battle Against Training Data Duplicates: Implementing MinHash LSH at Scale

3 min read

Rhea Kapoor

Jul 21

Benchmark Realities: How Vector Databases Actually Perform in Production

3 min read

Rhea Kapoor

Jul 14

The Practical Tradeoffs of Extreme Vector Compression: Testing RaBitQ at Scale

3 min read

Rhea Kapoor

Jul 14

The Practical Tradeoffs of Extreme Vector Compression: Testing RaBitQ at Scale

3 min read

Rhea Kapoor

Jul 10

When Millions Need Answers: Building Sub-50ms Search for Unstructured Data

2 min read

Rhea Kapoor

Jul 7

What Scaling Semantic Search Taught Me About Vector Database Tradeoffs

3 min read

Rhea Kapoor

Jul 3

The Reality of Scale: What Billion-Transaction Systems Teach Us About Vector Databases

2 min read

Rhea Kapoor

Jun 30

Lessons from Rexera: Why Vector Database Architecture Makes or Breaks AI Agents

3 min read

Rhea Kapoor

Jun 26

The Engineering Tradeoffs Behind HNSW-Based Vector Search

3 min read

Rhea Kapoor

Jun 23

Pushing Billion-Scale Vector Search Beyond RAM Limits with DiskANN

2 min read

Rhea Kapoor

Jun 19

Building Scalable AI Agents: Why Your Vector Database Choice Matters

2 min read

Rhea Kapoor

May 27

Milvus or FAISS? What I Learned Building a High-Performance Vector Search Engine

3 min read

Rhea Kapoor

May 23

What I Learned from Benchmarking Elastic Cloud vs. Zilliz Cloud for Vector Search

3 min read

Rhea Kapoor

May 21

Milvus vs Pinecone: A Comprehensive Comparison for AI-Powered Recommendation Engines in E-Commerce

5 min read

Rhea Kapoor

May 20

Vector Database Showdown: Architectural Insights for AI Developers

2 min read

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Writing Debut

Vector Databases Under the Hood: Practical Insights from Automotive Data Implementation

Why Our Vector Search Broke at 2M Queries/Day—And What Fixed It

I Discovered What Matters When Scaling Workflow Automation

My Battle Against Training Data Duplicates: Implementing MinHash LSH at Scale

Benchmark Realities: How Vector Databases Actually Perform in Production

The Practical Tradeoffs of Extreme Vector Compression: Testing RaBitQ at Scale

The Practical Tradeoffs of Extreme Vector Compression: Testing RaBitQ at Scale

When Millions Need Answers: Building Sub-50ms Search for Unstructured Data

What Scaling Semantic Search Taught Me About Vector Database Tradeoffs

The Reality of Scale: What Billion-Transaction Systems Teach Us About Vector Databases

Lessons from Rexera: Why Vector Database Architecture Makes or Breaks AI Agents

The Engineering Tradeoffs Behind HNSW-Based Vector Search

Pushing Billion-Scale Vector Search Beyond RAM Limits with DiskANN

Building Scalable AI Agents: Why Your Vector Database Choice Matters

Milvus or FAISS? What I Learned Building a High-Performance Vector Search Engine

What I Learned from Benchmarking Elastic Cloud vs. Zilliz Cloud for Vector Search

Milvus vs Pinecone: A Comprehensive Comparison for AI-Powered Recommendation Engines in E-Commerce

Vector Database Showdown: Architectural Insights for AI Developers