MongoDB targets AI’s retrieval problem

For all their technical capabilities, large language models (LLMs) still have a memory problem. They can lack the ability to retain context across conversations, and don’t always contain the frameworks to let them access relevant data, ultimately making their results unreliable and untrustworthy. NoSQL database pioneer MongoDB is taking on this problem, releasing new persistent…

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Databricks launches AiChemy multi-agent AI for drug discovery

Databricks has outlined a reference architecture for a multi-agent AI system, named AiChemy, that combines internal enterprise data on its platform with external scientific databases via the Model Context Protocol (MCP) to accelerate drug discovery tasks such as target identification and candidate evaluation. These early-stage steps are critical in drug development because they help pharma…

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Oracle adds pre-built agents to Private Agent Factory in AI Database 26ai

Oracle has added new prebuilt agents to Private Agent Factory, its no-code framework for building containerized, data-centric agents within AI Database 26ai. These agents include a Database Knowledge Agent, a Structured Data Analysis Agent, and a Deep Data Research Agent.   While the Database Knowledge Agent translates natural-language prompts into queries to fetch specific facts, policies,…

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MariaDB taps GridGain to keep pace with AI-driven data demands

MariaDB, the company behind the open-source fork of MySQL, is planning to acquire in-memory computing middleware provider GridGain to bolster its platform for high-performance data and artificial intelligence (AI) workloads. The database provider is planning to infuse its relational database with the California-headquartered startup’s in-memory technology, which it says will enable its database offerings to…

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