Literal Labs develops fast, energy-efficient, and explainable AI using logic-based models that can run anywhere – from small IoT devices to enterprise systems.
See our guide to this year’s hottest new businesses and most exceptional founders in the complete 2026 Startups 100 index.
Founders: Professor Alex Yakovlev, and Professor Rishad Shafik
Year founded: 2023
Website:literal-labs.ai
The rise of artificial intelligence (AI) technology has seen thousands of businesses adopt their own solutions to make their processes faster, smarter, and easier to manage. However, AI has a less than favourable reputation when it comes to sustainability, particularly because of its large energy and water consumption.
Not only that, but the lack of explainability and transparency in many AI models means people often don’t know why the model made a certain decision, risking user trust.
Newcastle University professors Alex Yakovlev and Rishad Shafik founded Literal Labs to solve these problems by developing logic-based AI models that are faster, more energy-efficient, and inherently explainable.
The process is simple: you give the system your dataset, which then figures out the best model setup. From there, you can deploy it anywhere – from tiny edge devices to regular computers – without needing expensive Graphics Processing Units (GPUs) or cloud servers.
“We scale AI down to efficient, logic-based solutions which can be deployed anywhere from the edge to cloud servers without compromising on accuracy,” says Yakovlev. “This combination of speed, efficiency, and explainability makes us uniquely positioned to deliver sustainable and ethical AI in resource-conscious markets.”
Yakovlev and Shafik’s groundbreaking approach saw Literal Labs secure £4.6m in pre-seed funding in a round led by venture capital (VC) firm North Gritstone in June 2025. Four months later, it was nominated for a national AI Innovation Award.
We scale AI down to efficient, logic-based solutions which can be deployed anywhere.
As for personal milestones, the North East-based company successfully proved that its Logic-Based Network (LBN) can run on tiny coin-cell powered Internet of Things (IoT) devices for up to ten years.
“That milestone felt little more than theoretical when we started, yet it was achieved with our logic-based models running AI inference every five seconds,” Yakovlev explains. “It was the perfect demonstration of our vision: AI that doesn’t just work, but works without waste.”
The startup’s ambitions for the next five years are lofty. Yakovlev and Shafik aim for Literal Labs to power the intelligence behind millions of divides and decision systems worldwide – delivering fast, efficient, and trustworthy AI everywhere.
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