Posts tagged with "Azure AI Search"

Industrial documents arrive as scanned paper, multilingual procedures, and proprietary CAD exports. Azure AI Search skillsets turn them into queryable text with structured metadata. This post walks the OCR, entity, language, and custom skill patterns that make the difference between a searchable index and one that actually answers technical queries.

Generic LLM copilots are a liability in manufacturing. Technicians need answers that cite the exact procedure, not plausible-sounding text. Retrieval-augmented generation grounded in Azure AI Search solves this when architected correctly. This is the pattern that holds up under service-bay pressure.

Automotive technical documentation is uniquely structured: ECU specs, wiring diagrams, service manuals, diagnostic codes, recall notices — all layered across vehicle platforms, model years, and markets. Azure AI Search handles this at scale if the index schema and retrieval pattern match the domain. This post walks the automotive-specific design choices.

Pure keyword search misses semantic matches. Pure vector search misses exact part numbers. Hybrid search combines both. This post explains the rank fusion and semantic re-ranking choices that turn a hybrid Azure AI Search query from "works on demos" into a production retrieval layer for manufacturing knowledge bases.

Manufacturing corpora mix scanned paper, CAD exports, work instructions, and supplier specs. Making them searchable with high recall and precision requires a thoughtful Azure AI Search skillset and indexer design. This post walks through the OCR, entity extraction, chunking, and semantic ranking choices that separate production-quality indexes from POCs.

Microsoft renamed Azure Cognitive Search to Azure AI Search in late 2023 and added substantial vector, semantic, and agentic-retrieval capabilities. Manufacturing teams running legacy Cognitive Search deployments need a structured migration plan — not a like-for-like upgrade, but a targeted modernisation of the features that matter most.

Manufacturing document processing is a high-volume, high-format-diversity problem. Azure AI Search (formerly Azure Cognitive Search) is the Microsoft-native platform that fits it well when configured correctly. This post walks through the architecture patterns that actually ship at industrial scale.

Agents need context. Discover Foundry IQ—the knowledge layer connecting AI agents to enterprise data with multi-source RAG orchestration, retrieval steering, dynamic security controls, and agentic RAG delivering 36% higher accuracy than traditional search.

Microsoft Ignite BRK193: Build agents with Azure AI Search knowledge features. Connect to SharePoint, web, blob. Hybrid search (keyword+vector+semantic), agentic retrieval with query planning, reasoning effort modes, Foundry IQ with MCP protocol. Code-focused implementation guide.