Matt Brailsford, lead developer on the Umbraco AI project at Umbraco HQ, discusses integrating AI into the Umbraco back office. He showcases a podcasting demo, illustrating AI's capabilities in transcription, summarization, and guest validation. Brailsford emphasizes Umbraco AI's extensibility for custom solutions, encouraging community engagement and experimentation.
Umbraco Automate integration for Umbraco.AI.Agents
Connects the Umbraco backoffice AI features (prompts, agents, Copilot, embeddings) to any OpenAI-compatible self-hosted server such as Ollama, LM Studio or vLLM — no cloud account required.
AI Agent Memory for Umbraco — persistent memory + learning layer for Umbraco's AI agent stack.
Jason Prothero introduces the ProWorks Umbraco.AI Page Evaluator, an open-source tool that enhances website content quality by providing structured feedback on clarity, SEO, and brand alignment. Integrated within Umbraco, it allows for efficient evaluation of pages before publication, reducing the risk of inaccuracies and ensuring brand consistency.
2026-05-07 from 14:00 to 20:00 (Europe/Stockholm) - Camelonta, Hammarby Kajgata 12, Stockholm, SE
2026-05-12 from 14:00 to 20:00 (Europe/Copenhagen) - Ecreo, Stærmosegårdsvej 8, Odense, DK
2026-05-14 from 18:00 to 21:00 (Europe/London) - Novicell UK, 21-33 Great Eastern Street, London, GB
Matt Brailsford announces the integration of speech-to-text functionality in Umbraco.AI, enhancing user interaction with new microphone features in Copilot and Tiptap. This capability allows users to dictate content seamlessly, supported by a management API and a dedicated service for developers. Future enhancements may include real-time transcription and text-to-speech features.
In this Umbracoffee episode, hosts chat with Matt Brailsford about Umbraco AI—covering Claude usage, semantic search, uploads, speech-to-text, and its evolution into a flexible, provider-agnostic framework for AI-powered CMS development.
2026-05-07 from 14:00 to 20:00 (Europe/Stockholm) - Camelonta, Hammarby Kajgata 12, Stockholm, SE
Matt Brailsford discusses the integration of Microsoft.Extensions.AI (M.E.AI) and the Microsoft Agent Framework (MAF) in developing AI capabilities for Umbraco. The use of IChatClient and middleware patterns enabled efficient feature development and agent orchestration, allowing for scalable, transferable skills while maintaining a cohesive architecture.
Matt Brailsford discusses the implementation of guardrails in Umbraco.AI, which are safety policies that evaluate content before and after AI model interactions. Guardrails consist of evaluators, phases, and actions to manage inappropriate content. They are customizable and essential for maintaining content integrity in AI-driven systems.
In the video, Paul Seal demonstrates how to use Umbraco AI to create and publish a fully structured article in about 20-30 seconds. He showcases the tool's ability to automatically populate content blocks, insert quotes, and add images, highlighting its potential to enhance editorial workflows on Umbraco 17.
Experimental community Browser AI provider for Umbraco AI.
Matt Brailsford introduces Umbraco.AI.Search, a semantic vector search add-on for Umbraco that enhances search capabilities by understanding user intent rather than relying solely on keyword matching. This tool addresses limitations of traditional searches, supports multilingual queries, and integrates with Umbraco.Cms.Search, offering improved content discovery and related content features.
Matt Brailsford discusses the new file upload feature in Umbraco.AI, allowing users to drag and drop documents into Copilot. The system supports various file types, enabling text extraction from Office documents and direct processing of images and PDFs. The extensible architecture allows for additional file formats to be integrated seamlessly.
2026-04-21 from 13:00 to 14:30 (America/New_York) - Online
Matt Brailsford discusses the Umbraco.AI.Prompt package, detailing how content editors can utilize prompt templates for AI-generated tasks like SEO titles and alt text. He explains the syntax, available variables, and the importance of using the image: prefix for image prompts, alongside practical examples and tips for maximizing AI capabilities.