Grace Ashiru
A South Africa-founded startup is making the case that the AI industry’s default answer to the energy crisis — building bigger, burning more — is the wrong approach entirely, and has secured $5 million in seed funding to prove it.
The round was led by California-based climate technology investor VoLo Earth Ventures. Founded in 2025 by Viroshan Naicker, Siddharth Gutta, and Mathew Haswell, Refiant AI builds tools that compress and restructure AI models to make them more efficient, lowering the computational requirements of AI systems while maintaining performance and allowing them to run on smaller devices or local infrastructure.
The company’s headline result illustrates the scale of what’s possible: Refiant compressed a 120 billion parameter AI model — one of the most powerful open-source models available — to run on a MacBook Pro with just 12GB of RAM.
The AI sector is facing a mounting energy crisis. Global data centre power consumption is expected to double by 2028, driven largely by the explosive growth of large language models and generative AI workloads. In response, major technology companies are projected to spend nearly $700 billion in 2026 alone on building infrastructure to sustain AI development.
Refiant’s team already includes a former Google Cloud architect, a Cambridge PhD researcher, and an engineer with NASA experience. The company is in active discussions with several multinational technology firms exploring how its approach could reduce their AI compute costs while maintaining data and energy sovereignty.
For Africa specifically, Refiant believes the continent’s AI ambitions are currently bottlenecked by limited data centre infrastructure and reliance on foreign cloud providers — making the case for efficient, locally-runnable AI models particularly compelling in the region.
VoLo Earth Ventures’ Joseph Goodman said the fundamental constraint on AI is not demand but energy, and that Refiant’s approach replaces brute-force scaling with a more efficient, nature-inspired architecture that lowers energy use while increasing capability.
