Airtop Raises $25.0M Series

MetricLy

MetricLy uses Artificial Intelligence and Machine Learning to help Interior Designers better know their clients preferences, streamline material selections, curate custom specifications and build accurate budgets that saves them 10X the time and costs.

Mercatus Technologies Inc

Leading grocers with 5 to 500 stores use Mercatus to run their digital storefronts, fulfill orders for pickup and delivery, personalize rewards and loyalty offers, and ultimately achieve omnichannel profitability.

Elsevier | Mendeley

Mendeley brings your research to life, so you can make an impact on tomorrow.

SingleStore

The core of all AI, business intelligence and applications is data — various bits and bytes that come in all different formats. Only when we sift through this data, reason with it and build on top of it in real time does it give way to vast amounts of information and knowledge. Real-time insights are key to the way we live our lives today; the way we entertain ourselves; the way we listen to music; the way we order groceries. Real-time insights keep your BI tools fresh; they keep your ride-sharing app with the most current price; and they ensure you never miss a fraudulent payment. SingleStoreDB is the world’s only database that empowers users to transact, analyze and search data in real time. It empowers the world’s makers to build, deploy and scale modern, intelligent applications — backed by streaming data ingestion, a unique table type that supports both transactional (OLTP) and analytical (OLAP) workloads, limitless point-in-time recovery and a distributed (shared-nothing), MySQL-compatible architecture.

Matillion

In 2025, Matillion introduced Maia, the industry’s first AI Data Automation platform for building data products without limits. The core of Maia consists of tightly integrated components, each designed to support data teams as they move from maintenance to ownership. - Maia Team brings an always-on set of expert AI agents that handle the repetitive, time-consuming data work—building, modifying, optimizing, and maintaining pipelines as systems evolve—freeing teams to focus on higher-value outcomes without losing control. - Maia Context Engine captures business rules, standards, and institutional knowledge, ensuring data products remain transparent, reusable, and deterministic as they evolve. - Maia Foundation provides the enterprise backbone, with security, governance, observability, and scale built in from the start. This design ensures compliance with data regulations and maintains trust, so teams can move fast without compromising control or risking data security. Together, these components remove the constraints that slow data teams down.