The PointFire Blog

Microsoft is introducing a new way to create and publish content in SharePoint: HTML pages. Users can create HTML pages with Copilot or upload existing HTML files, but three challengesstand in the way of making them available in multiple languages.

You know your SharePoint multilingual content needs work. The challenge is showing what it will take to close the gap.

Microsoft Copilot can work in multiple languages: it can understand prompts in supported languages, respond in those languages, and use content written in one of many languages as grounding material. The harder problem is cross-language retrieval: a user may have prompted Copilot in Spanish while the best source content exists only in English, and Copilot may not reliably find that source content before it tries to answer.

For years, we've helped organizations build, translate, and manage multilingual SharePoint sites. One thing keeps coming up: many teams don't know where they have gaps in their multilingual content and UI.

The next generation of web applications will be built for people and AI agents at the same time. This is the idea behind the dual-use web powered by WebMCP: every application, every page has a human interface and an agent interface. Humans interact through the UI, while AI agents discover and invoke the application's capabilities directly.

While working on an upcoming free app that will audit your multilingual SharePoint sites for missing, outdated, mislabeled, or orphaned translations, I ended up reverse-engineering parts of Syntex Translation that I haven't seen documented anywhere.

If you've ever looked at the hidden columns in the Site Pages library after enabling multilingual publishing, you may have noticed that SharePoint and PointFire's multi-page model use different columns to manage language versions.

Delivering effective multilingual search in M365 is more complicated than it seems. Do you translate everything first then search, or search then translate, or translate the query? What do M365 search engines already know about languages?

Let's explore some of the lesser-known features of SharePoint and Microsoft Search that go beyond exact matching, as well as some examples of how the Search Optimizer, an extension to PnP Modern Search, improves your search queries to overcome the missing features.

Making SharePoint multilingual isn’t just about turning on translation—it requires planning, governance, and clear workflows to avoid inconsistent content and user frustration. Without the right structure, organizations quickly face duplicated effort, broken experiences, and loss of trust in multilingual content. By designing with language in mind and embedding translation into everyday publishing, SharePoint can become a reliable, scalable multilingual platform.

Large language models are often assumed to outperform traditional neural machine translation, but research continues to show a more nuanced reality. While LLMs produce more fluent and natural sounding text, NMT systems still tend to deliver slightly better accuracy across large datasets. Microsoft’s new Azure AI Translator preview introduces LLM-based translation options alongside traditional NMT, raising new questions about when each approach works best. This article revisits the LLM vs NMT debate and tests how models like GPT-4o perform when translating idioms.

SharePoint search has evolved from a basic keyword engine to a complex, multi-layered system, with Modern Search and Copilot adding personalization and AI capabilities. Unlike web search engines, SharePoint search is driven by metadata, permissions, and context, which can make results vary depending on who, where, and when you search. Tools like PnP Modern Search and PointFire Search Summarizer extend SharePoint’s capabilities, using AI to deliver more relevant, task-focused results with clear explanations of why each document matters.

SharePoint’s native features alone can’t fully meet language compliance requirements under laws like Canada’s Official Languages Act. Learn how to ensure your SharePoint environment stays fully compliant, auditable, and bilingual by design.

PointFire Search Optimizer now includes query rewriting, enhancing SharePoint search by expanding acronyms, correcting typos, and interpreting natural language, all while keeping full transparency and control in your hands. Unlike Copilot’s opaque process, you always see exactly how your query is improved.

If you think that Microsoft Search in SharePoint and other M365 products isn't as good as it used to be, you could be right. Microsoft has been quietly disabling search features in the past couple of years.

A decade ago, we built a SharePoint translation memory that uncovered a massive hidden flaw in Microsoft’s Machine Translation Service. Here’s the untold story of why it never launched.

Microsoft 365 Copilot doesn’t fail at random—its limits are predictable. This article explains how Copilot really searches and how you can avoid blind spots.

Microsoft 365 Copilot relies on more than just ChatGPT. Behind the scenes, multiple large language models handle semantic indexing, re-ranking, and text generation to deliver search results. Understanding these hidden LLMs explains why Copilot’s answers are powerful, but also why they differ from classic SharePoint search.

Copilot isn’t a true replacement for SharePoint Search. Learn where Copilot helps, where it fails, and why SharePoint Search remains essential.

Compare M365 Copilot and PointFire Search Optimizer for SharePoint. See why PointFire Search Summarizer delivers faster, more accurate, query-focused results.

Say that you would like to have a link in your SharePoint page, for instance in the navigation, that goes to a different place depending on the user’s language. How do you do it? This article is a comprehensive how-to to get this done.

AI and modern solutions have already and will soon transform SharePoint search tools. We explore what the future holds for this evolving technology.

Struggling with SharePoint search? Employees waste up to 30% of their work time searching for information, leading to frustration and lost productivity. Traditional search enhancements help, but they don’t fix the biggest issue—sifting through results. Discover how PointFire Search Summarizer streamlines the process with AI-powered summaries, saving time and effort.

This is a detailed guide on how to enable multilingual features in SharePoint. It details all the things you need to do in 5 areas: Alternate languages, Multilingual Page Publishing, term sets, content types and user profiles.

PointFire people talk about the difference between translation and localization quite a bit because there are two sets of products: (1) PointFire Translator which does translation of content and (2) PointFire 365 which does localization of the user interface. But what does that mean, really? When you look at a SharePoint screen, what fits into the category of translation and what fits into the category of localization?

This how-to guide details the steps to change users Microsoft 365 profile language without Delve

Wouldn't it be great if there was to make SharePoint searched more efficient? Discover the search summarizer, a tool that gives you AI summaries of every one of your search results. The summaries tell you what each document says about your search query. This product is an extension of the open source PnP search project.