Tailos is pioneering the future of autonomous cleaning technology, leveraging AI-powered robotics to modernize facility maintenance across hospitality, retail, and commercial spaces. Tailos’ intelligent robot vacuums combine advanced perception, real-time localization, and autonomous navigation to deliver consistent, high-efficiency cleaning—helping businesses reduce labor costs while improving space hygiene and operational productivity.

MP Software Ventures partnered with Tailos to design cutting-edge simulation and testing environments using Unreal Engine to model photorealistic real-world scenarios. These blackbox, AI-driven simulated environments enable the robots to “learn” thousands of edge-case cleaning situations—including obstacles, variable lighting, floor textures, furniture layouts, and multi-room navigation—before deployment in commercial settings. This dramatically accelerates training cycles, reduces real-world testing risks, and enhances the robot’s predictive intelligence.

Through this collaboration, MP Software Ventures engineered scalable pipelines for spatial computing, object detection and robotic path-planning, enhancing Tailos’ ability to operate autonomously with higher precision. The simulated environments also enabled robust validation of vacuum performance ensuring that the robot adapts intelligently to real-world complexities such as tight corners, carpets vs. hardwood transitions, threshold detection and dynamic obstacle avoidance.
With MP Software Ventures’ support, Tailos is redefining the standard for smart cleaning systems, empowering businesses to adopt AI-driven automation seamlessly. Together, we are shaping the next generation of autonomous service robots delivering reliability, efficiency and intelligence at scale.