Literal Labs

Faster, leaner, explainable AI models for decision intelligence and business intelligence platforms.

The page explains how ModelMill trains models for edge AI deployment on MCUs, CPUs, and embedded systems without cloud, GPU, or data center.

Logic-Based Networks replace neurons with logic, delivering faster, more efficient, deterministic, and explainable AI.

The page compares Literal Labs’ logic-based AI models, their performance, and their applications.

The company explains that enterprise AI success depends on data readiness, including quality, lineage, governance, and deployment constraints.

For over 30 years, members of Literal Labs team have been active in their research of on-device, edge AI.

Explore REDRESS, a groundbreaking edge AI approach reducing Tsetlin Machines' memory and power needs, making advanced AI accessible for low-power devices.

Thought leadership, technical perspectives, and practical guidance from Literal Labs on logic-based AI, efficient inference, enterprise AI, and machine learning deployment.

The page examines logic-based AI, decision intelligence, and their potential impact on the future of work.

Literal Labs CEO explains how Tsetlin Machines offer energy-efficient AI with logic and learning combined.

Noel Hurley joins BritChips to discuss energy-efficient AI, semiconductors, and the logic behind Literal Labs.

Literal Labs closes a £4.6m pre-seed round to bring logic-based AI to market. The raise was covered by The Times and backed by Northern Gritstone.

Join Literal Labs to build energy-efficient AI with logic-based AI — help shape the future of scalable, low-power machine learning.

Explore ModelMill pricing. Base platform fee, training credits, and deployment royalty. Train logic-based AI models for edge hardware — no GPU required.

Jem Davies. Ex-Arm Fellow, GPU pioneer, and ML expert. Now Non-Executive Director at Literal Labs, shaping future tech innovations.

Kelvin Harrison. Seasoned tech executive, startup mentor, and Literal Labs Board Observer. Expert in scaling IT and telecom ventures.

Leon Fedden. AI pioneer and CTO at Literal Labs. Former AstraZeneca AI leader, driving innovation in deep learning and generative models.

Literal Labs is a UK AI startup that developed a new class of AI requiring no GPU or data center and producing no hallucinations. The team behind LBNs and ModelMill is introduced.

Literal Labs' colour palette, usage guidelines, and accessibility standards ensuring all communications meet WCAG compliance standards.

Comprehensive component guidelines and technical specifications for the Literal Labs design system, ensuring consistency and quality.

The page provides header styles, layouts, and usage guidelines for Literal Labs and its products, including ModelMill.

The page offers contact information for the Literal Labs team regarding AI models, partnerships, or general inquiries.

Find answers to common questions and get support for Literal Labs and ModelMill. Access documentation and troubleshooting resources.

Train Logic-Based AI models for edge devices, MCUs, and 32-bit semiconductors. 54× faster, 52× less energy than neural networks. No GPU. ModelMill by Literal Labs.

Literal Labs’ candidate privacy policy explains how personal data is handled during job applications.

Literal Labs’ privacy policy describes how the company collects, uses, and protects user data on literal-labs.ai and its products.

The page lists Literal Labs’ legal documents, policies, and terms, emphasizing transparency and regulatory compliance.

The page outlines the terms and conditions for using ModelMill’s LBN training service, including rights and responsibilities.

A list of trademarks owned and used by Literal Labs, including the Literal Labs name, logo, and associated brand assets.

GitHubRepository owner

Noel Hurley, former ARM executive, joins Literal Labs to advance logic-based AI solutions for edge computing. The company targets long-standing challenges in the edge AI sector. Hurley brings semiconductor expertise to develop hardware-software systems for efficient, scalable AI deployment at the edge.

Sep 2025Tech.euNews article

Northern England’s **Northern Gritstone** leads a funding round for a university spinout developing energy-efficient, logic-based AI systems. Co-lead **Mercuri** and backers including **Sure Valley Ventures** and **Cambridge Future Tech SPV** support the project, which aims to advance low-power AI solutions for media, entertainment, and broader tech applications.

Jun 2025Press OfficeNews article

Literal Labs secures £4.6 million in pre-seed funding to advance its logic-based AI technology, designed for lower energy consumption. The company targets global deployment of its energy-efficient AI solutions, differentiating from traditional machine learning approaches.

Jun 2025Business WireNews article