ActionAI, a startup focused on building reliability infrastructure for enterprise AI systems, announced it has raised $10 million in seed funding to address trust, accuracy, and accountability challenges in AI deployment. The round was led by UAE-based investors.
Founded by Miriam Haart, ActionAI is developing a platform designed to ensure AI systems can be safely deployed in mission-critical environments. The company plans to use the funding to scale its technology and expand adoption across industries where reliability and compliance are essential.
The company is targeting a growing gap in enterprise AI adoption, where usage is increasing but trust remains a major barrier. Many organizations continue to keep AI initiatives in pilot stages due to concerns around inaccuracies, hallucinations, and lack of oversight. ActionAI’s platform is designed to address these issues across the full AI lifecycle, from data inputs to production monitoring.
Its infrastructure enables granular testing and evaluation of AI systems, real-time debugging to identify failures, and human-in-the-loop controls through its Explainable Exceptions framework to mitigate hallucinations. The platform also includes monitoring tools that detect performance issues and automatically respond to changes in data or instructions, helping ensure consistent and reliable outputs.
ActionAI is focused on industries such as finance, manufacturing, retail, insurance, supply chain, and legal systems, where errors in AI outputs can have significant operational or regulatory consequences. By enabling transparent and accountable AI-driven automation, the company aims to help enterprises reduce inefficiencies and unlock broader adoption of AI technologies.
KEY QUOTES
“AI is handling increasingly complex tasks with highly sensitive or personal data without any sufficient oversight or accountability. ActionAI makes AI accountable from day one. Beginning with the initial data inputted, we review, fine-tune and secure the information which underpins an AI system. From there, our reliability architecture prevents AI vulnerabilities well before they reach production. Which enables AI automations with transparency and trust.”
“Enterprises are facing the dichotomy of implementing AI while accepting the unreliability which goes alongside it. As AI improves, we need to ensure it can be trusted. This is what ActionAI is delivering: secure, transparent, reliable AI for mission-critical enterprise use-cases.”
Miriam Haart, CEO, ActionAI
