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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.

Bloomreach launches Personalized Media in-Grid

November 13, 2025 /

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

November 6, 2025 /

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

October 8, 2025 /

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

September 18, 2025 /

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

June 17, 2025 /

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

Algolia unveils AI Agents for Salesforce and Adobe

May 8, 2025 /

Algolia, a AI-native search and discovery platform, announced a new AI agent experience that illustrates how autonomous systems can act on real-time data across enterprise platforms. Demonstrated using Salesforce’s Agentforce and integrated with Adobe Experience Manager (AEM), Adobe Experience Platform (AEP), and Salesforce Commerce Cloud (SFCC), Algolia shows what’s possible when agents are equipped with live, structured context, without latency or hallucination.

Algolia semantically interprets user intent, retrieves structured content from its index containing data from multiple customer datastores, and assembles context-aware responses in real time—bridging the gap between front-end agent platforms like Agentforce and the backend systems that hold critical content and customer signals.

Algolia handles this orchestration through its AI-native search engine, which retrieves the most relevant information from its index, content that has been ingested and structured from platforms like Adobe Experience Manager (AEM), Salesforce Commerce Cloud (SFCC), and Adobe Experience Platform (AEP). Whether surfacing personalized media, live product availability, or behavioral attributes, Algolia assembles responses that reflect the full customer context and returns them in milliseconds. The result is an agent experience that feels intuitive, precise, and deeply responsive to user needs.

https://www.algolia.com/about/news/algolia-unveils-new-real-time-context-aware-ai-agents-across-salesforce-and-adobe

OpenSearch releases OpenSearch 3.0

May 6, 2025 /

The OpenSearch Software Foundation, the vendor-neutral home for the OpenSearch Project, announced the general availability of OpenSearch 3.0. OpenSearch 3.0 enables users to increase efficiency, deliver superior performance, and accelerate AI application development via new data management, AI agent, and vector search capabilities.

Vector engine features:

  • GPU Acceleration for OpenSearch Vector Engine: Delivers superior performance for large-scale vector workloads while significantly lowering operational spend by reducing index building time.
  • Model Context Protocol (MCP) support.
  • Derived Source: Reduces storage consumption by removing redundant vector data sources and utilizing primary data to recreate source documents.

⠀Data management features:

  • Support for gRPC: Enables faster and more efficient data transport and data processing for OpenSearch deployments.
  • Pull-based Ingestion: Enhances ingestion efficiency and gives OpenSearch more control over the flow of data and when it’s retrieved by decoupling data sources and data consumers.
  • Reader and Writer Separation: Ensures consistent, high-quality performance for indexing and search workloads by configuring each in isolation.
  • Apache Calcite Integration.
  • Index Type Detection: automatically determining whether an OpenSearch index contains log-related data and speeding up log analysis feature selection.

Other updates include: Lucene 10, Java 21 minimum supported Runtime, and Java Platform Module System Support.

https://opensearch.org/blog/unveiling-opensearch-3-0

Elastic’s Cloud Serverless now on Google Cloud Marketplace

April 24, 2025 /

From the Elastic blog…

Today, we are excited to announce the general availability of Elastic Cloud Serverless on Google Cloud — now available in the Iowa (us-central1) region. Elastic Cloud Serverless provides the fast way to start and scale observability, security, and search solutions without managing infrastructure. Built on the Search AI Lake architecture, which leverages Google Cloud Storage, it combines storage, separate storage and compute, low-latency querying, and advanced AI capabilities.

  • No compromise on speed or scale: Elasticsearch Serverless dynamically scales to accommodate your workload, handling unpredictable traffic spikes automatically — all while delivering low-latency search on boundless object storage.
  • Hassle-free operations: Say goodbye to managing clusters, provisioning nodes, or fine-tuning performance. Free your team from operational tasks — no need to manage infrastructure, do capacity planning, upgrade, or scale data. 
  • Purpose-built product experience: Elastic Cloud Serverless offers a streamlined workflow to help you create projects tailored to your unique use cases in observability, security, and search. With guided onboarding, you can use in-product resources and tools that guide you every step of the way, accelerating time to value.
  • Flexible usage-based pricing model: Elastic Cloud Serverless offers a usage-based pricing model that scales with your needs.

https://www.elastic.co/blog/elastic-cloud-serverless-google-cloud-general-availability

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