Maisa is a system that enhances the performance of AI and large language models by making them more transparent, traceable, and programmable. It offers automation through accountable, self-learning AI agents, called digital workers, that users can instruct via natural language, allowing those agents to navigate company knowledge, access tools orAPIs, and execute steps with clear, auditable logic. At its core lies the Knowledge Processing Unit (KPU), a reasoning kernel that orchestrates multi-step workflows, handles error recovery, and maintains an evident chain of execution. This architecture delivers automation with clarity and process-level traceability, enabling businesses to deploy AI-driven workflows more efficiently and reliably.

Ziplines Education, an industry-leading education company, partners with universities to deliver industry-focused certificate courses that prepare professionals for today’s digital-first workforce so individuals can confidently pursue the career they’ve always wanted. The award-winning industry innovator launched in 2017 as GreenFig and relaunchedas Ziplines Education in early 2024. Today, dozens of leading U.S. colleges and universities trust Ziplines Education as their continuing education partner, including the University of Virginia School of Continuing and Professional Studies, Texas Tech University, and the University of North Carolina at Charlotte. To learn more about the company, visit ziplines.com and follow them on @ZiplinesEducation on Linkedin, Facebook, Instagram, and YouTube, and on @ZiplinesEdu on Twitter.

Developer of an AI-powered HR platform intended to automate hiring processes, improve candidate match quality, engage talent across multiple channels, and provide organizational insights. The company's AI-native system integrates with existing HR workflows to eliminate manual tasks and data silos, enabling HR teams to focus on strategic initiatives, accelerate time to hire, enhance candidate engagement, and deliver actionable analytics for organizations that employ at scale.