Founder & CEO
Tim Li
Turning agricultural research into practical field intelligence.
Tim Li is the founder and CEO of Mutus Tech, a UK agricultural technology company building practical tools for fertiliser planning, pest intelligence, crop monitoring and field-level evidence.
He leads company strategy, research and technical direction, and remains closely involved in the architecture and development of Parallel Farm, Pezego and the shared data and AI systems behind them.
- 17+ years
- Software, data and technology R&D
- 2021
- Founded Mutus Tech
- MSc
- Advanced Computer Science
- Liverpool
- Based in the United Kingdom
Founder story
Why I founded Mutus
I have spent more than 17 years working in computer science, software development and data systems. Before founding Mutus Tech, my work included commercial data processing, analytics, visualisation, enterprise software and large-scale data infrastructure.
One conversation changed the direction of that work. A farm manager asked whether AI could help optimise fertiliser use.
The question sounded straightforward, but the decision was not. Fertiliser planning depends on soil conditions, crop requirements, weather, previous applications, expected yield, environmental impact, economics and the realities of farm operations. A useful answer required more than an algorithm. It required a way to connect evidence, context and action.
That experience made one point clear: agriculture did not simply need another isolated model or software demonstration. It needed practical systems that could connect scientific research, field records and day-to-day decisions within the same workflow.
I founded Mutus Tech in Liverpool in 2021 to bring together software engineering, data science and agricultural research around that challenge. Since then, we have developed Parallel Farm and Pezego and worked with farms, universities, agricultural organisations and industry partners through UK and international R&D projects.
Every field trial, deployment and user conversation adds to what we know. That is essential in agriculture, where useful technology must be tested over time and under real operating conditions.
“Agriculture needs more than isolated AI demonstrations. It needs practical systems that connect scientific evidence, field records and everyday decisions.”
Leadership
What I lead at Mutus
As founder and CEO, I am responsible for the overall direction of Mutus Tech and remain directly involved in research, technology and product development.
Company direction
I set strategic priorities, focusing on agricultural problems where user need, supporting evidence and a realistic route to adoption come together.
Research and development
I turn research questions into technical plans, coordinate delivery with academic and industry partners, and work to ensure funded R&D creates reusable capabilities beyond an individual project.
Product and technology
I oversee Parallel Farm, Pezego and the shared data, AI and reporting infrastructure behind them, including software architecture, data integration, analytical models and AI services.
Partnerships and commercialisation
I work with farms, universities, agricultural businesses and technology partners to define use cases, organise validation and establish practical routes from pilots to continued adoption.
Research into use
From research to working products
Research is valuable to Mutus when it can be carried into practical and repeatable use.
Parallel Farm supports fertiliser planning, crop monitoring, field tasks, records and evidence reporting. Pezego provides mobile pest identification, contextual crop intelligence and structured field observations.
Behind both products is shared infrastructure designed to keep information connected to the same field, crop and growing season. Field data, funded R&D, partner review and peer-reviewed research contribute to the evidence base behind the products.
The aim is not to turn every research output into a feature. It is to identify capabilities that solve a defined problem, can be validated properly and have a credible route into sustained use.
Working principles
Principles that shape the work
Practical before promotional
Technology should solve a defined problem for a real user. A successful demonstration is useful, but it is not the same as a reliable product that fits an agricultural workflow.
Evidence before claims
Agricultural technology should be clear about its assumptions, limitations and level of validation. We state where evidence is still developing.
Technology should support judgement
AI should not hide uncertainty or replace the professional judgement of farmers, agronomists and scientists. It should organise information and present relevant evidence.
Direction
The next stage for Mutus
Mutus is moving from a strong research and technical foundation towards sustained adoption. Our priorities are to improve product usability and reliability, expand field validation, strengthen the connection between user requirements and product development, and establish commercial models that support continued investment.
We are also bringing fertiliser planning, pest observations, crop monitoring, field tasks and evidence reporting closer together. These activities are often managed separately, even though they relate to the same field, crop and growing season.
Our long-term ambition is to build a trusted agricultural intelligence platform that brings together field records, scientific models, environmental data and practical farming knowledge. The objective is not to automate every agricultural decision, but to give farmers, advisers and agricultural organisations clearer records and better access to relevant evidence.
I remain directly involved in this work and will continue to focus Mutus on areas where our technology can create measurable practical value.
Background
Professional background
Tim has more than 17 years of experience in computer science, software R&D, data analysis and technology business management.
Before founding Mutus Tech, he worked on commercial data processing, analytical and visualisation platforms, enterprise software systems and large-scale data infrastructure.
He holds an MSc in Advanced Computer Science from the University of Liverpool. His current work spans software and data architecture, applied artificial intelligence, agricultural decision-support systems, research commercialisation and technology strategy.
Areas of expertise
- Software architecture
- Applied AI
- Agricultural data
- Decision support
- Research commercialisation
Building the next stage of Mutus
Start a practical conversation.
Tim welcomes conversations with farms, agricultural businesses, universities, research institutions and technology partners interested in practical applications of AI and data in agriculture.