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Author: Chandan

Vector Databases: From Hype to Production Reality – Part 4: Building RAG Applications on Azure
AI/ML Databases Azure Cloud Computing

Vector Databases: From Hype to Production Reality – Part 4: Building RAG Applications on Azure

December 18, 2025December 7, 2025

Theory becomes reality in this part. We move from understanding vector databases and comparing options to actually building a production-ready Retrieval Augmented Generation application on

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Azure AI Search, retrieval augmented generation, implementation, Azure OpenAI, rag, production deployment, pgvector
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Vector Databases: From Hype to Production Reality – Part 3: The Vector Database Landscape
Azure Cloud Computing AI/ML Databases

Vector Databases: From Hype to Production Reality – Part 3: The Vector Database Landscape

December 17, 2025December 7, 2025

With the technical foundations established in Parts 1 and 2, we now face the practical question every development team encounters: which vector database should we

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Qdrant, Chroma, Azure SQL, database comparison, pgvector, vector databases, Pinecone, Milvus, Weaviate
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Vector Databases: From Hype to Production Reality – Part 2: Architecture and Indexing Algorithms
Azure Cloud Computing AI/ML Databases

Vector Databases: From Hype to Production Reality – Part 2: Architecture and Indexing Algorithms

December 16, 2025December 7, 2025

In Part 1, we explored what vector databases are and why they have become essential infrastructure for AI applications. Now we dive into the technical

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quantization, vector databases, database architecture, HNSW, IVF-PQ, indexing algorithms, hybrid search
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TTS Forge: Build Your Custom Voice Cloning Pipeline with XTTS v2
AI Machine Learning Python Open Source

TTS Forge: Build Your Custom Voice Cloning Pipeline with XTTS v2

December 15, 2025December 15, 2025

Build a complete voice cloning pipeline that trains custom TTS models on consumer hardware. TTS Forge demonstrates end-to-end voice synthesis from recording through inference using XTTS v2 and VITS models.

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Coqui TTS, speech synthesis, deep learning, PyTorch, audio processing, text-to-speech, voice cloning, TTS, XTTS v2
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Vector Databases: From Hype to Production Reality – Part 1: Understanding Vector Databases
Azure Cloud Computing AI/ML Databases

Vector Databases: From Hype to Production Reality – Part 1: Understanding Vector Databases

December 15, 2025December 7, 2025

The artificial intelligence landscape has undergone a seismic shift in recent years, and at the center of this transformation lies a technology that most developers

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database architecture, machine learning, embeddings, rag, Azure AI, Semantic Search, vector databases
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Database Integration: MCP for Azure PostgreSQL and pgvector
Azure Cloud Computing Programming Database AI & Machine Learning

Database Integration: MCP for Azure PostgreSQL and pgvector

December 14, 2025November 28, 2025

Throughout this series, we have explored Model Context Protocol fundamentals, Azure MCP Server capabilities, custom server development, and multi-agent orchestration. Now we focus on one

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Vector Search, Semantic Search, Database Integration, MCP Server, AI Embeddings, Azure Database for PostgreSQL, pgvector
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Azure AI Agent Service with Model Context Protocol
Azure Cloud Computing Programming AI & Machine Learning

Azure AI Agent Service with Model Context Protocol

December 13, 2025November 28, 2025

In the previous posts, we explored the Model Context Protocol fundamentals, examined Azure MCP Server’s capabilities, and built custom MCP servers on Azure. Now we

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Multi-Agent Systems, Agent Orchestration, A2A Protocol, MCP Integration, Enterprise AI, Azure AI Foundry, Azure AI Agent Service
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Building Custom MCP Servers on Azure
Devops Azure Cloud Computing Programming

Building Custom MCP Servers on Azure

December 12, 2025November 28, 2025

In the previous posts, we explored the Model Context Protocol as a universal standard and examined how Microsoft’s Azure MCP Server enables AI agents to

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Azure Container Apps, api development, typescript, c#, Custom MCP Server, docker, Serverless, Azure Functions, Python
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Azure MCP Server: Connecting AI Agents to Azure Resources
Azure Cloud Computing Programming AI & Machine Learning

Azure MCP Server: Connecting AI Agents to Azure Resources

December 11, 2025November 28, 2025

In the previous post, we explored the Model Context Protocol as a universal standard for connecting AI systems with external data sources. Now we turn

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Natural Language Management, AI Agents, GitHub Copilot, Microsoft Entra ID, Azure MCP Server, Azure Services, Cloud Integration
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Understanding Model Context Protocol: The Universal Standard for AI Integration
Cloud Computing Programming AI & Machine Learning

Understanding Model Context Protocol: The Universal Standard for AI Integration

December 10, 2025November 28, 2025

The artificial intelligence landscape has transformed dramatically over the past year, with large language models becoming increasingly sophisticated in their reasoning capabilities. However, even the

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Development Tools, azure, MCP, Model Context Protocol, AI Integration, Enterprise AI, JSON-RPC, Protocol Standards
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Posts pagination

1 2 … 49 Next

Recent Posts

  • Vector Databases: From Hype to Production Reality – Part 4: Building RAG Applications on Azure
  • Vector Databases: From Hype to Production Reality – Part 3: The Vector Database Landscape
  • Vector Databases: From Hype to Production Reality – Part 2: Architecture and Indexing Algorithms
  • TTS Forge: Build Your Custom Voice Cloning Pipeline with XTTS v2
  • Vector Databases: From Hype to Production Reality – Part 1: Understanding Vector Databases

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