Unikie has launched a new AI Lab to accelerate the real-world adoption of artificial intelligence (AI) for its customers and further embed AI across its own product and software development operations. With a strategic vision grounded in practical experience, the lab is set to become the centerpiece of Unikie’s AI expertise.
EvoChip.ai, a pioneer reinventing machine learning architectures, today announced AltiCoreAI, an advanced model training and inference IP block that achieves unprecedented improvements in inference speed and efficiency. Designed to excel both as software on standard platforms and as custom hardware logic, AltiCoreAI delivers orders-of-magnitude faster AI inference while operating on minimal datasets.
Openlayer, a unified platform enabling evaluation and governance of AI systems at the enterprise scale, today announced the close of a $14.5 million Series A funding round. The round was led by Race Capital, with participation from NXTP, KPN Ventures, Mindset, Y Combinator, Quiet Capital, and Telefonica. The fresh capital will support Openlayer’s plans to enhance its enterprise-grade product capabilities and expand go-to-market efforts across key global industries.
Rockwell Automation has announced the successful deployment of its industrial AI technology at PVO-Vesivoima’s hydroelectric plants in Finland. The cutting-edge solution leverages real-time data, AI, and machine learning to optimize turbine performance, enhance grid stability, and meet new regulatory demands in Finland’s energy sector. This marks a significant advancement in AI-driven industrial automation applied to critical infrastructure.
TensorStax, a leading autonomous AI agentic platform for data engineering, has raised $5 million in Seed funding led by Glasswing Ventures, with additional participation from Bee Partners and S3 Ventures. The funding will accelerate the company’s product development and expand its footprint in the rapidly growing field of agentic AI for data engineering. This investment comes at a time when the global market for agentic AI in data engineering is expected to grow significantly, reaching $66.7 billion by 2034, according to Market.us.
Franz Inc., a pioneer in Artificial Intelligence (AI) and a leading provider of Graph Database technology, has unveiled AllegroGraph v8.4, an advanced release that features an enhanced AI-powered Natural Language Query (NLQ) interface. This update propels the development of Agentic AI by enabling more intuitive, human-like interaction between users and intelligent systems, essential for autonomous agents capable of reasoning, planning, and acting autonomously.
Standard Bots, an American robotics leader, has officially expanded its operations with a new 16,000-square-foot manufacturing facility in Glen Cove, New York. This move, which doubles the size of its previous Long Island location, highlights the company’s commitment to scaling its American-made robotics production. In addition to the facility expansion, Standard Bots debuted a new 30kg payload, 2m reach robot at The Automate Show, further solidifying its position as a key player in the automation industry.
Alation Inc., a leader in data intelligence, has launched the Data Products Builder Agent, an AI-powered tool designed to transform raw, under-documented data into trusted, reusable data products. With increasing pressure on data teams to deliver fast, reliable, and AI-ready data for both human and machine consumption, this new solution automates key aspects of the data product lifecycle, empowering organizations to manage their data more efficiently and strategically.
Verseon has made significant strides in artificial intelligence, presenting two cutting-edge papers at the 2025 IEEE Conference on Artificial Intelligence. The first paper introduces an innovative technique for handling imperfect data, allowing AI models to maintain predictive accuracy even when faced with missing or erroneous data. The second paper reveals a new methodology, AutoESSV, that dynamically selects the optimal ensemble strategies for combining multiple AI models. Both advances are poised to enhance AI’s real-world utility, particularly in data-scarce environments.
