docs(architect): weekly KB update — 106 files refreshed (2026-04)

Updates across all 5 skills: ms-ai-advisor, ms-ai-engineering,
ms-ai-governance, ms-ai-security, ms-ai-infrastructure.

Key changes:
- Language Services (Custom Text Classification, Text Analytics, QnA):
  retirement warning 2029-03-31, migration guides to Foundry/GPT-4o
- Agentic Retrieval: 50M free reasoning tokens/month (Public Preview)
- Computer Use: Claude Sonnet 4.5 (preview) + OpenAI CUA models
- Agent Registry: Risks column (M365 E7), user-shared/org-published types
- Declarative agents: schema v1.5 → v1.6, Store validation requirements
- MLflow 3: 13 built-in LLM judges, production monitoring, Genie Code
- AG-UI HITL: ApprovalRequiredAIFunction (C#) + @tool(approval_mode) (Python)
- Entra ID Ignite 2025: Agent ID Admin/Developer RBAC roles, Conditional Access
- Security Copilot: 400 SCU/month per 1000 M365 E5 licenses, auto-provisioned
- Fast Transcription API: phrase lists, 14-language multi-lingual transcription
- Azure Monitor Workbooks: Bicep support, RBAC specifics
- Power Platform Copilot: data residency (Norway/Europe → EU DB, Bing → USA)
- RAG security-rbac: 4-approach table (GA + 3 preview access control methods)
- IaC MLOps: Well-Architected OE:05 principles, Bicep/Terraform patterns
- Translator: image file batch translation Preview (JPEG/PNG/BMP/WebP)

All 106 files: Last updated 2026-04 | Verified: MCP 2026-04

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

plugins/ms-ai-architect/skills/ms-ai-engineering/references/rag-architecture/multimodal-rag.md

@@ -1,6 +1,6 @@
 # Multimodal RAG — Bilder, tabeller og dokumenter i RAG
 
-**Last updated:** 2026-02
+**Last updated:** 2026-04 | Verified: MCP 2026-04
 **Status:** GA (Document Intelligence, Content Understanding), Preview (multimodal embeddings)
 **Category:** RAG Architecture & Semantic Search
 
@@ -309,3 +309,17 @@ chartFormat=markdown
 | Multimodal RAG with Vision (ISE DevBlog) | **Verified** | [devblogs.microsoft.com](https://devblogs.microsoft.com/ise/multimodal-rag-with-vision/) |
 | RAG Time Journey 4: Advanced Multimodal Indexing | **Verified** | [techcommunity.microsoft.com](https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/rag-time-journey-4-advanced-multimodal-indexing/4397300) |
 | Azure-Samples/multimodal-rag-code-execution | **Baseline** | [github.com](https://github.com/Azure-Samples/multimodal-rag-code-execution) |
+
+
+### Azure AI Search Multimodal Pipeline (oppdatert 2026-04)
+
+Azure AI Search multimodal pipeline (GA) støtter nå en fullstendig 5-stegs prosess:
+1. **Ekstraksjon** — Document Extraction, Document Layout, eller Content Understanding skill
+2. **Tekst-chunking** — Text Split skill for håndterbare biter
+3. **Bildebeskriving** — GenAI Prompt skill verbaliserer bilder via LLM
+4. **Embedding** — Azure OpenAI, Microsoft Foundry, eller Azure Vision embedding
+5. **Bildestoring** — Knowledge store lagrer ekstraherte bilder for annotation i klientapp
+
+Hybrid queries kombinerer full-text search, vector search, og semantic ranking for å svare på spørsmål der svaret befinner seg i et innebygd diagram i en PDF.
+
+**Querytidsstøtte:** GenAI Prompt skill-baserte pipelines støtter hybrid queries over tekst og verbaliserte bilder. For bilde-til-vektor-queries (søk med bilde som input), bruk Azure Vision multimodal embedding skill med en tilsvarende vectorizer.