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Day: May 6, 2025

Bloomreach adds marketing and e-commerce features

Bloomreach, an agentic platform for personalization, announced features to transform AI-driven personalization and customer engagement across marketing and product discovery. From workflows to conversational search, these features highlight agentic AI.

Marketing:

  • Autonomous Marketing Agents: AI-powered agents to help marketers automate and execute the entire campaign creation process.
  • Recommendations+ : Analyzes each customer’s journey and behavior in real-time to recommend products that align with a customer’s preferences.
  • Contextual Personalization: Automates personalization through the delivery of individualized emails, mobile messages and onsite experiences to each customer.

⠀Conversational Shopping:

  • Search Triggered Conversations: Launches a personalized conversation directly from the search bar and acts as an integrated shopping assistant.
  • Embedded Conversations: Brings Clarity’s conversational capabilities directly to Product Detail Pages (PDPs) and Product Listing Pages (PLPs).

⠀Search:

  • Personalization Studio: Learns from live customer signals and optimizes in real-time to reflect current shopper intent.
  • Ranking Studio: Gives practitioners control to integrate critical business signals like margins or offline sales into search algorithms.
  • Multi-language search: Expands global reach by extending autonomous search across 33 supported languages.
  • Conditional Slot Merchandising: Elevates product placement by allowing the merchandiser to define their own business-driven conditions so AI can autonomously populate product grids and placements.

https://www.bloomreach.com/en/news/2025/bloomreach-unveils-the-features-ushering-in-the-agentic-era-of-marketing-and-ecommerce/

OpenSearch releases OpenSearch 3.0

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

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