Maisa AI Raises $25M to Tackle Enterprise AI's Massive Failure Rate
Maisa AI secures $25 million in seed funding to combat the 95% failure rate of enterprise generative AI pilots by introducing accountable digital workers. The startup's new platform replaces opaque black boxes with transparent, supervised AI processes.
A recent MIT report reveals that 95% of corporate generative AI pilots fail, prompting a shift toward more reliable agentic systems. Maisa AI, a year-old startup, addresses this crisis by building accountable AI agents instead of opaque black boxes. The company secures $25 million in a seed round led by European VC firm Creandum to scale its innovative approach to enterprise automation.
Unlike standard vibe-coding platforms, Maisa focuses on building the actual process required to reach a response through a method it calls "chain-of-work." The startup deploys a system known as HALP, or human-augmented LLM processing, which interactively outlines each step of a task with human supervision. Additionally, Maisa utilizes a deterministic Knowledge Processing Unit (KPU) specifically designed to limit AI hallucinations.
This emphasis on trustworthiness attracts major enterprise clients, including a large bank and companies in the car-manufacturing and energy sectors. By ensuring that humans can easily review work completed at rapid speeds, Maisa positions itself as a highly advanced alternative to traditional robotic process automation. The startup ultimately aims to unlock significant productivity gains without forcing companies to rely on rigid, pre-defined rules.