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Category: Content management & strategy (Page 1 of 482)

This category includes editorial and news blog posts related to content management and content strategy. For older, long form reports, papers, and research on these topics see our Resources page.

Content management is a broad topic that refers to the management of unstructured or semi-structured content as a standalone system or a component of another system. Varieties of content management systems (CMS) include: web content management (WCM), enterprise content management (ECM), component content management (CCM), and digital asset management (DAM) systems. Content management systems are also now widely marketed as Digital Experience Management (DEM or DXM, DXP), and Customer Experience Management (CEM or CXM) systems or platforms, and may include additional marketing technology functions.

Content strategy topics include information architecture, content and information models, content globalization, and localization.

For some historical perspective see:

https://gilbane.com/gilbane-report-vol-8-num-8-what-is-content-management/

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/

Snowflake to acquire Datometry Migration Solution

From the Snowflake blog…

We’re thrilled to announce Snowflake has entered into a definitive agreement to acquire the technology powering the Datometry software migration solution, which makes moving from legacy data warehouses like Teradata to Snowflake up to four times faster while reducing costs by 90%. This new venture will enable our current and future customers to accelerate their data journey with faster migrations.

Datometry’s solution translates queries, scripts and workloads in real time, allowing applications built for legacy systems to run on Snowflake with minimal code changes.

We’re eager to start integrating the power of Datometry into SnowConvert AI. In addition to bringing Datometry’s capabilities to Snowflake, we’re thrilled to also welcome many talented Datometry employees, including Datometry founder and CEO Mike Waas, CTO Michael Duller, and VP of Customer Success Rima Mutreja. With their deep knowledge and expertise, we’re looking forward to collaborating to bring innovative developments in data migration to the Snowflake AI Data Cloud.

Snowflake’s free solutions, SnowConvert AI and Snowpark Migration Accelerator, reduce migration risks and costs and simplify code conversion to help customers realize more value from their data from day one.

https://www.snowflake.com/en/blog/accelerate-data-migration-datometry-technology

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

Sitecore unveils SitecoreAI

Sitecore announced SitecoreAI, a digital experience platform that puts artificial intelligence at the center of marketing. As customer journeys shift from static search to AI-driven discovery.

Built on Sitecore XM Cloud, SitecoreAI unifies content, data, and personalization in a single, composable SaaS platform designed to optimize as teams work – helping marketers launch faster, spend smarter, and improve performance through AI-enabled workflows. At its core is the Agentic Studio, a workspace where marketers and AI collaborate to plan, create, and personalize experiences. The Agentic Studio debuts with 20 AI-powered agents that automate complex workflows from campaign planning to content migration, production and testing – and gives marketers and their agency partners the flexibility to design their own agents and flows using simple visual tools.

Within the Agentic Studio, Agentic Flows orchestrate multi-step personalized campaigns from briefing and experimentation through publishing and optimization. Spaces enable real-time collaboration between people and AI, turning disconnected tools into a coordinated system supporting continuous improvement.

Running on Microsoft Azure, SitecoreAI is the evolution of XM Cloud, unifying content management, customer data, personalization, and search in one platform that adapts through configuration and human feedback. For current XM Cloud customers, the upgrade is seamless – no migration required.

https://www.sitecore.com/company/newsroom/press-releases/2025/10/sitecore-unveils-sitecoreai-ushering-in-the-ai-first-era-of-digital-experience

Adobe delivers new AI assistants and models across Creative Cloud

Adobe announced new AI features across Creative Cloud apps including Photoshop, Lightroom, Premiere, and Illustrator. The updates focus on improving efficiency, precision, and control for creative professionals.

Highlights include the AI Assistant in Photoshop, which can handle repetitive tasks, provide personalized recommendations, and support conversational editing while allowing seamless switching to manual tools. Photoshop also gains Generative Fill with partner models, Generative Upscale using Topaz Labs and other partners, and Harmonize for blending objects naturally into scenes. Premiere introduces AI Object Mask, shape-based masking tools, and Fast Vector Mask in public beta for faster video editing. Lightroom receives an AI Assisted Culling feature to help manage large photo collections.

Firefly enhancements include Image Model 5 in public beta for 4MP photorealistic generation and editing, Prompt to Edit for natural language adjustments, and planned Layered Image Editing. Firefly Boards adds Rotate Object for 2D-to-3D perspectives, PDF export, and batch image downloads. Firefly Creative Production supports no-code batch editing of thousands of images. Firefly Custom Models let users create personalized models for stylistically consistent outputs.

Many features are in public or private beta, with partner models from Google, Black Forest Labs, Topaz, and others integrated directly into Adobe apps, available to Creative Cloud Pro and Firefly plan subscribers.

https://news.adobe.com/news/2025/10/adobe-max-2025-creative-cloud

MariaDB unveils unified cloud database platform

MariaDB plc announced the availability of MariaDB Enterprise Platform 2026, a database platform for building next-generation intelligent applications. This new release reduces complexity by unifying transactional, analytical and AI (vector) database engines into a single platform. With the addition of retrieval-augmented generation (RAG) pipelines and AI agents, MariaDB Enterprise Platform is designed to create a strategic advantage for enterprises building agentic applications. Instead of complex, slow data pipelines, AI agents can now autonomously access data and extract critical insights from MariaDB’s cloud-native, serverless platform instantly.

  • Built-in RAG: MariaDB Enterprise Platform 2026 introduces a native “RAG-in-a-Box” solution. MariaDB AI RAG enables the grounding of large language models (LLMs) with context from the data stored in MariaDB.
  • Embedded AI Copilots: MariaDB’s AI copilots are ready-to-use agents inside MariaDB’s platform allowing agentic applications to interact with data through natural language. Available via MariaDB Cloud, preconfigured agents include a developer and a DBA AI copilot. The developer copilot is a Text-to-SQL agent connected to MariaDB’s database that responds to natural language queries with insights on the data stored in your database.
  • Integrated MCP Servers: The Model Context Protocol (MCP) Servers enable AI Agents to interact with MariaDB databases and other databases across the enterprise.

https://mariadb.com/newsroom/press-releases/mariadb-unveils-unified-cloud-database-platform-designed-to-accelerate-agentic-ai-application-development

Bloomreach and Uniform unveil turnkey conversational commerce framework

Bloomreach, an agentic platform for personalization, and Uniform, a composable digital experience platform, today announced a turnkey AI solution unveiled at the MACH Alliance’s AI Hackathon taking place from October 21-22. Powered by the Open Data Model from MACH Alliance, the solution showcased how composable technology and generative AI can be seamlessly combined, enabling any brand to build conversational experiences that help them retain control of their customer relationships.

Built on AWS, the solution aggregates product catalogs from multiple commerce platforms through Uniform, and enriches them with AI-driven tagging, normalization, and metadata optimization. Then, the product data flows into Bloomreach Clarity, where it powers a fully conversational shopping interface — allowing customers to browse, compare, and shop via natural dialogue. 

https://www.bloomreach.com/en/news/2025/bloomreach-and-uniform-to-unveil-new-turnkey-conversational-commerce-framework/https://www.uniform.devhttps://machalliance.org

Graphwise launches Graph AI Suite

Graphwise, announced Graph AI Suite, a comprehensive Graph AI platform that accelerates how businesses unlock value from their data. It turns enterprise knowledge into a self-improving engine for trustable AI by leveraging GraphRAG. The platform’s capabilities simplify how organizations build intelligent knowledge graphs that continuously learn at scale.

  • Modeling & Mapping: Allows organizations to build a graph from structured and unstructured data, including automated taxonomy building. It helps them mature from “text on a document” toward “structured content” and, eventually, a knowledge graph, improving GraphRAG performance.
  • Ingestion & Automation: These components connect to arbitrary systems and support specific use cases for each organization, enabling integration with LLMs such as Gemini, Llama, and others and agentic AI platforms.
  • Semantic Analysis: Automatically moves content toward a knowledge graph by creating taxonomies and enterprise vocabularies. It drives semantic metadata enrichment across data silos, building the basis for a highly accurate GraphRAG infrastructure. A key part of the AI Flywheel, it makes the platform easy for subject matter experts to use.
  • GraphRAG: This is the Graph AI Suite’s core capability for delivering trustworthy AI. It uses the knowledge graph to furnish the LLM accurate, context-rich and semantically relevant data, mitigating hallucinations and ensuring responses are grounded in verifiable facts.

http://www.graphwise.ai/

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