Applied AI · Digital transformation · Founder of Ayima

AI and technology leadership that improves how businesses operate and what they build.

Founder of Ayima, with twenty years of running technology-led operations and delivering digital change. Combining commercial and operational experience with practical technical knowledge.

Mike Nott
Brands worked with at Ayima
About

Mike Nott

Founder, operator and engineer. Based in Oxford, working with teams in the UK, North America and Asia.

I build applied AI for organisations: LLM agents that work from years of company knowledge, automation that removes manual steps from real operations, and the data and infrastructure layers that keep those systems reliable in production.

That focus comes from two decades of digital transformation in practice. I founded Ayima in 2007 and ran it as Chief Operating Officer, building the operations, in-house technology and international footprint that took it to over 200 people across five offices and public on Nasdaq. Ayima has since returned to a lean, senior-only consultancy, where I remain a founder.

Ayima’s clients have included Verizon, Wells Fargo, British Airways, Macy’s, Marks & Spencer, Sephora and O2, in some of the most competitive markets online, and its in-house tools have been used across the search industry.

  • AI strategy and application to business operations
  • LLM agents and applied AI systems
  • AI infrastructure and platform engineering
  • Product development and technology delivery
  • People management and team development
  • International operations
  • M&A due diligence and integration
  • Board-level leadership and governance
Projects

Current work

Ayima AI

An SEO agent for enterprise teams, built on Ayima’s methodology and knowledge base and connected to the industry’s leading data sources. It runs analysis, diagnoses problems and recommends what to do next.

ayima.ai

Public tools

Open-source tools for AI agents and local models: web access for agents, token-efficient home automation, and front-ends for self-hosted inference. Each one started as something needed in production and is released for others to run on their own infrastructure.

github.com/mike-nott

Local inference

Running sovereign LLMs on-premise where privacy, security or cost make cloud APIs the wrong fit: hardware selection, vLLM deployments on dedicated machines, model evaluation, and tool-calling agents that keep corporate data inside the business.

Contact

Get in touch

To discuss AI, technology and business operations, or board and advisory roles.