Refiant Raises $5m to Cut AI Energy Use as Data Centre Demand Surges

South African-founded startup, Refiant AI, has raised $5 million in seed funding to reduce the energy needed to run artificial intelligence systems, as global demand for data centres surges.

The funding round was led by VoLo Earth Ventures, which focuses on climate-related technologies. The company said the investment will help it grow its team, build its platform and strengthen talks with large technology firms.

Spending on data centres is expected to reach nearly $700 billion this year, driven largely by AI workloads. At the same time, energy use from these facilities is projected to double by 2028.

Refiant is trying to tackle that problem by making AI models smaller and less power-hungry. The company said it has already compressed a 120 billion parameter model so it can run on a standard laptop. Normally, such a model would require far more powerful hardware.

According to the company, the compressed version runs on a MacBook Pro with 12GB of memory. It keeps between 95% and 99% of its original performance. It can also run alongside another model on the same device.

Sid Gutta, co-founder of Refiant, said: “AI’s growing energy footprint is one of the most urgent and underappreciated challenges in the climate space. The industry’s default answer is to build more data centres and consume more power. Ours is to make the AI itself dramatically more efficient.”

The company, based in California, said it tested energy use inside a Faraday cage to ensure accurate readings. Under those conditions, the system reached about 3,000 tokens per kilowatt-hour.

That is up to 100 times more efficient than running the same model in a traditional data centre.

In practical terms, the energy used for one AI task on standard infrastructure could handle about 100 similar tasks using Refiant’s approach.

The founders argue that improving efficiency is a better long-term path than expanding infrastructure. Running AI locally on smaller machines could also help organisations avoid sending data to large cloud providers, which usually means higher costs and less management.

Recent developments from Google have pointed in a similar direction. Its TurboQuant compression method reduced memory needs significantly, reinforcing interest in making models leaner rather than simply scaling hardware.

Dr Viroshan Naicker, co-founder of Refiant, said: “The AI industry is spending hundreds of billions scaling infrastructure when the real breakthrough is the ability to do more with radically less. Nature doesn’t build by brute force. Evolution optimises. We’ve applied that principle to AI, and the results speak for themselves.”

The company believes its work could also help businesses balance AI adoption with environmental targets.

Mathew Haswell, another co-founder, said: “Those two mandates don’t have to be in tension. AI adoption and sustainability commitments can coexist, but only if the technology itself becomes more efficient. 

“Organisations shouldn’t have to choose between deploying AI and meeting their energy targets – and they shouldn’t have to send their data halfway around the world to do it.”

Joseph Goodman, managing partner at VoLo Earth Ventures, added: “AI’s biggest constraint isn’t demand, it’s energy. What’s been missing is a fundamentally more efficient way to compute.

“Refiant’s architecture replaces brute-force scaling with a far more efficient, nature-inspired approach that lowers energy use while increasing capability. That’s the kind of breakthrough needed to make AI sustainable on a global scale.”

Refiant said it is already in discussions with several multinational firms. It plans to push its technology further, with a focus on stronger compression, longer context handling and better tracking of how models operate.

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