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Category: Enterprise search & search technology (Page 1 of 62)

Research, analysis, and news about enterprise search and search markets, technologies, practices, and strategies, such as semantic search, intranet collaboration and workplace, ecommerce and other applications.

Before we consolidated our blogs, industry veteran Lynda Moulton authored our popular enterprise search blog. This category includes all her posts and other enterprise search news and analysis. Lynda’s loyal readers can find all of Lynda’s posts collected here.

For older, long form reports, papers, and research on these topics see our Resources page.

Elastic adds high-precision multilingual reranking to new Elastic Inference Service

Elastic, a Search AI Company, made two Jina Rerankers available on Elastic Inference Service (EIS), a GPU-accelerated inference-as-a-service that makes it easy to run fast, high-quality inference without complex setup or hosting. These rerankers bring low-latency, high-precision multilingual reranking to the Elastic ecosystem.

Rerankers improve search quality by reordering results based on semantic relevance, helping surface the most accurate matches for a query. They improve relevance across aggregated, multi-query results, without reindexing or pipeline changes. This makes them valuable for hybrid search, RAG, and context-engineering workflows where better context boosts downstream accuracy. The two new Jina reranker models are optimized for different production needs:

Jina Reranker v2 (jina-reranker-v2-base-multilingual)
Built for scalable, agentic workflows.

  • Low-latency inference with strong multilingual performance.
  • Ability to select relevant SQL tables and external functions that best match user queries..
  • Scores documents independently to handle arbitrarily large candidate sets.

Jina Reranker v3 (jina-reranker-v3)
Optimized for high-precision shortlist reranking.

  • Optimized for low-latency inference and efficient deployment in production settings.
  • Strong multilingual performance; maintains stable top-k rankings under permutation.
  • Cost-efficient, cross-document reranking: v3 reranks up to 64 documents together in a single inference call, reasoning across the full candidate set to improve ordering when results are similar or overlapping.

https://ir.elastic.co/news/news-details/2026/Elastic-Adds-High-Precision-Multilingual-Reranking-to-Elastic-Inference-Service-with-Jina-Models/default.aspx

Upland announces BA Insight Platform with integrated AI search experiences for enterprises

Upland Software, Inc., a provider of AI-powered knowledge and content management software, announced the Upland BA Insight Platform. The new BA Insight Platform incorporates SmartHub, ConnectivityHub, AutoClassifier, Smart Preview, and Connectors to deliver search experiences that are more connected, more contextual, and more actionable. Features include:

  • Knowledge Graphs to deliver deeper, connected, and more contextualized insights by mapping relationships across complex datasets
  • Agentic Retrieval-Augmented Generation (RAG) to provide more accurate answers to complex questions through conversational AI interfaces
  • Amazon Q Business Integration to enable users to connect and perform generative actions against organizational content via the seamless AI-powered assistant

BA Insight introduces native integrations with Amazon Q Business and AWS generative AI assistant, enabling organizations to unlock conversational search and gain actionable insights across all content sources, securely. By working closely with AWS, BA Insight ensures customers benefit from seamless deployment, robust security, and continuous innovation, empowering organizations to maximize the value of their information and accelerate their AI journey. The unified BA Insight enterprise search and AI enablement platform is available in AWS Marketplace.

https://investor.uplandsoftware.com/news/news-details/2026/New-Upland-BA-Insight-Platform-Delivers-Integrated-AI-Search-Experiences-for-Enterprises/default.aspx

Algolia and Microsoft collaborate on retail experiences

Algolia, an AI Search and Retrieval Platform, today announced a collaboration with Microsoft to provide retailers and brands with greater influence, accuracy, and visibility in AI-driven shopping experiences. The collaboration integrates Algolia’s real-time enriched product attributes (product data, inventory availability, and product pricing) into Microsoft Copilot, Microsoft Bing Shopping, and Microsoft Edge, to help retailers ensure their products appear correctly and competitively across emerging AI discovery surfaces.   

Algolia customers gain greater influence over how their products are represented across Microsoft digital sites. Retailers benefit from enhanced brand control and stronger context awareness within Copilot, Bing Shopping, and Edge, backed by fresher, deeper, and more accurate product data.  

AI-driven discovery becomes shoppable through real-time, retailer-approved data, giving merchants influence over external, “off property” AI surfaces. Retailers can now extend their merchandising strategies into LLM environments that were previously inaccessible. 

Algolia, with the help of Microsoft, is address critical gaps in agentic commerce, more dynamic product storytelling, and deeper insights into how products perform across Microsoft experiences for richer reporting and retail media measurement. 

https://www.algolia.com/about/news/algolia-collaborates-with-microsoft-to-drive-real-time-product-data-to-shopping-experiences

Bloomreach launches Personalized Media in-Grid

Bloomreach, an agentic platform for personalization, introduced Personalized Media in-Grid, a new capability that turns static product grids into intelligent storytelling surfaces, powered by its AI-powered search solution Bloomreach Discovery and amplified through its marketing and conversational shopping solutions. The feature transforms product-listing pages into dynamic, story-driven experiences, showcasing Bloomreach’s connected suite. Personalized Media in-Grid brings the compound value of the platform to life, uniting placement, personalization, and conversation inside the shopping journey.

Today’s product-listing pages are largely static and transactional. Personalized Media in-Grid changes that by allowing retailers to insert videos, images, buying guides, seasonal promotions, and cross-sell messages between products on search and category pages. With slot selection, in-context preview, audience targeting, and scheduling capabilities, merchandising teams can manage and optimize content, and

  • Blend storytelling with commerce: Insert rich media, buying guides, promotional banners, and cross-sell content directly into product grids at specific slots.
  • Manage content: Apply rules globally across queries or categories, preview in context, and schedule campaigns..
  • Target specific audiences: Deliver tailored messages by integrating with Bloomreach Engagement for segmentation and 1:1 personalization, and with Bloomreach Clarity for conversational experiences.
  • Measure impact: Track performance through Discovery’s built-in analytics and extend reporting through Engagement dashboards.

https://www.bloomreach.com/en/news/2025/bloomreach-unites-search-storytelling-and-personalization/

Google introduces the File Search Tool in Gemini API

From the Google technology developers blog…

Today, we’re launching the File Search Tool, a fully managed RAG system built directly into the Gemini API that abstracts away the retrieval pipeline so you can focus on building. File Search provides a simple, integrated and scalable way to ground Gemini with your data, delivering responses that are accurate, relevant and verifiable:

  • Integrated developer experience: automatically manages file storage, chunking strategies, embeddings and dynamic injection of retrieved context into prompts.
  • Vector search: to understand the meaning and context of user querys even if the exact words aren’t used.
  • Built-in citations: automatically included citations specify which parts of your documents were used to generate the answer.
  • Support for a wide range of formats: including PDF, DOCX, TXT, JSON and common programming language file types.

We’re making storage and embedding generation at query time free of charge. You only pay for creating embeddings when you first index your files, at a fixed rate of $0.15 per 1 million tokens (or whatever the applicable embedding model cost is, in this case gemini-embedding-001). This new billing paradigm makes the File Search Tool easier and cost-effective to build and scale with.

https://blog.google/technology/developers/file-search-gemini-api

commercetools Previews Cora

commercetools, an AI-first commerce platform for enterprises, announced a preview of commercetools Cora, an AI-native and multimodal shopping companion designed to demonstrate the future of conversational commerce. Cora shows how enterprises will be able to deliver human-like continuity across web, mobile, WhatsApp, and other channels. Shoppers can begin a journey on one device and continue it on another without losing context or progress. Cora maintains continuity and gives enterprises a branded companion they fully control.

Cora gives enterprises the practical tools to build loyalty and reduce drop-off by keeping every shopping journey connected. Key capabilities in the first phase of its launch include:

  • AI-First Product Discovery: Conversational search that understands vague requests (i.e., long queries) and translates them into relevant recommendations.
  • Omnichannel Continuity: Preserves context, cart state, and conversation history across all channels and devices.
  • Brand-Controlled Experience: Keeps shoppers inside a retailer’s ecosystem, ensuring that every interaction reflects the brand’s identity and builds lasting trust.

Cora is also fully white-labeled, allowing retailers to customize and brand the experience while relying on commercetools’ enterprise-grade security, governance, and data controls.

Cora will debut with AI-powered product search and launch in phases toward full agentic capabilities, including autonomous checkout.

https://commercetools.com/press-releases/commercetools-previews-cora

Google announces 10 new AI features for Chrome

From the Google Products Blog…

Today we share how we’re using the latest in Google AI to enhance your browsing experience. We’re building Google AI into Chrome across multiple levels so it can better anticipate your needs, help you understand more complex information and make you more productive when you browse the web:

1. Enhance your browsing with Gemini in Chrome

Starting today, we’re rolling out Gemini in Chrome to Mac and Windows desktop users in the U.S. with their language set to English, so you can ask Gemini to clarify complex information on any webpage (or webpages) you’re reading. It’ll be available to businesses in the coming weeks via Google Workspace with enterprise-grade data protections and controls. And we’re also bringing Gemini in Chrome to mobile in the U.S.

2. Get ready for your agentic browsing assistant

In the coming months, we’ll be introducing agentic capabilities to Gemini in Chrome. These will let Gemini in Chrome handle those tedious tasks that take up so much of your time, like booking a haircut or ordering your weekly groceries.

3. Make better sense of all your tabs

Gemini in Chrome can now work across multiple tabs, so you can quickly compare and summarize information across multiple websites to find what you need.

4. Find webpages you previously visited

For those frustrating instances when you want to jump back into a past project but don’t want to scroll through your history to find an important website you previously visited, soon you’ll be able to use Gemini in Chrome to recall it for you.

5. Work with your Google apps without changing tabs

We’ve also built a deeper integration between Gemini in Chrome and your favorite Google apps, like Calendar, YouTube and Maps, so you can schedule meetings, see location details and more without leaving the page you’re on.

6. Search with AI Mode right from the omnibox

You’ll have the option to quickly access Google Search’s AI Mode right from the Chrome address bar (what we call the omnibox) on your computer.

7. Ask questions and learn more about your current page

You can ask questions about the entire page you’re on right from the omnibox. Chrome can suggest relevant questions based on the context of the page to help you kickstart your search.

8. Combat more sophisticated scams with Gemini Nano

Safe Browsing’s Enhanced Protection mode already uses Gemini Nano to help identify tech support scams that try to trick you into downloading harmful software. Soon, we’ll be expanding this protection to also stop sites that use fake viruses or fake giveaways to trick you.

9. Say goodbye to dodgy notifications and unwanted permissions

Chrome now detects potentially spammy or scammy notifications and gives you the option of seeing them or unsubscribing. Since rolling out this feature, we’ve reduced unwanted website notifications for Chrome on Android users by around 3 billion each day.

10. Change compromised passwords in 1-step

Chrome already automatically and securely fills in your login credentials and proactively alerts you if any of your passwords are compromised. Very soon it’ll use AI as a password agent to go a step further, letting you change your saved passwords with a single click on supported sites.

https://blog.google/products/chrome/new-ai-features-for-chrome

Algolia introduces context-aware retrieval for agents

Algolia, an AI-native search and discovery platform, released its MCP Server, the first component in a broader strategy to support AI agents. This new offering enables large language models (LLMs) and autonomous agents to retrieve, reason with, and act on real-time business context from Algolia.

With the Algolia MCP Server, agents can access Algolia’s search, analytics, recommendations, and index configuration APIs through a standards-based, secure runtime. This turns Algolia into a real-time context surface for agents embedded in commerce, service, and productivity experiences. Additionally, Algolia’s explainability framework with its AI is included for enhanced transparency.

Algolia’s MCP Server is purpose-built for enterprise-grade agent orchestration, enforcing policy at the protocol layer to ensure agents operate within role- and context-sensitive boundaries. It provides end-to-end observability, making every agent-triggered decision fully traceable and inspectable. The platform also enables privacy-aware personalization that complies with regional regulations like GDPR and CCPA, without relying on invasive tracking.

Enterprise customers, developers, and partners can start building AI-native applications, copilots, and intelligent agents today. Algolia’s MCP Server supports Anthropic’s Model Context Protocol (MCP) and can be integrated with leading LLM runtimes.

https://www.algolia.com/about/news/algolia-introduces-context-aware-retrieval-for-the-agentic-era

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