Misti AI has raised $336,000 in a pre-seed funding round led by Fuel Ventures. The round remains open, with the company targeting a total of $673,000 to upgrade its artificial intelligence platform designed for industrial environments.

The platform is engineered to convert existing camera infrastructure into tools for real-time operational monitoring and insights, primarily targeting heavy industrial applications.

Misti AI has initiated preliminary deployments at remote mining and energy operations in Peru, with a specific focus on sites with limited network connectivity.

According to the company, its platform transforms video feeds into structured data, enabling real-time monitoring, safety compliance, and operational insights.

Heavy industries possess millions of cameras across mines, refineries, and logistics sites, but these systems are currently passive, fragmented, and underutilized. Misti AI is building an inference layer on top of this infrastructure to convert video into continuous, machine-readable intelligence, creating an observability platform akin to Datadog, but for the physical world.

Carlos Samame, Co-founder and CEO of Misti AI, stated, "We are entering the decade of physical AI. Every industrial site already has cameras installed, but they are blind systems, recording images without understanding the content. We are building the intelligence layer that enables machines to interpret, reason, and act on what is happening in the real world. We are starting with observability, but the long-term vision is to become the intelligent system for global physical operations."

Mark Pearson, Founder of Fuel Ventures, commented, "The vast camera networks in heavy industry represent the last untapped frontier of real-time operational data. Misti AI is not just creating a feature; it is defining physical observability—an entirely new, major category of infrastructure. We are leading this pre-seed round because Samame and his team, with their top-tier backgrounds and UK Tech Nation Global Talent status, have demonstrated the deep technical expertise and enterprise vision required to build this foundational layer."