Mutus Tech profiled by Innovate UK Business Connect

About this case study

This case study was researched and published by Innovate UK Business Connect on 1 April 2026, profiling Mutus Tech’s participation in the BridgeAI programme. The full article is published at iuk-business-connect.org.uk.

The summary below paraphrases the published article and adds Mutus Tech’s own framing of the engagement.

Company background

Mutus Tech is a UK precision-agriculture company founded by Tim Li. The company name references the Himalayan wild yak (Bos mutus), chosen to embody strength and resilience — qualities the team sees as central to building tools that hold up in real farm conditions.

Mutus Tech emerged from earlier work at Ant Data Limited, after a farm-manager client asked whether AI could help optimise fertiliser use. That question turned into the foundation of what is now the Mutus Tech operating layer.

Today the company has two core products:

• Parallel Farm — a field operating platform for fertiliser planning, soil-health monitoring, farm tasks, records and reports
• Pezego — an AI crop-and-pest-intelligence product, live on iOS and Android, supporting mobile pest detection, in-field diagnosis and crop-health monitoring

Both products are connected by the Mutus AI Platform — the shared data, AI and reporting infrastructure that links field boundaries, soil data, satellite imagery, climate data, pest image datasets, mobile workflows and partner-validated reporting workflows.

The BridgeAI engagement

Mutus Tech joined the BridgeAI programme, delivered by Innovate UK, and was enrolled in The Alan Turing Institute’s Independent Scientific Advisor programme. Through that pairing, Mutus Tech worked with:

• Professor Po Yang — University of Sheffield, as Independent Scientific Advisor
• Dr Qing Xue — Director of Product Management at Mutus Tech, leading the engagement on the Mutus side

The programme provided structured advisory access, technical review and the wider BridgeAI cohort for Mutus’s AI work.

What the evaluation showed

A structured evaluation of Pezego was carried out using 10 pest scenarios drawn from real field conditions. Compared with standard reference resources, Pezego delivered:

• +15% improvement in diagnostic accuracy — Pezego provided more context-specific advice, with refined interpretation of ambiguous pest descriptions
• −20% reduction in processing time — faster time-to-recommendation for the same scenarios

These results sit alongside Pezego’s peer-reviewed publication in the IEEE Internet of Things Journal (Volume 12, Issue 23 — DOI 10.1109/JIOT.2025.3586374), co-developed with RSK ADAS, the University of Sheffield and the University of Liverpool.

In their words

“Mutus Tech’s advanced, AI-driven agricultural data science solutions address some of the key challenges in modern farming.”

— Professor Po Yang, University of Sheffield

Dr Qing Xue (Director of Product Management at Mutus Tech) credited the BridgeAI guidance and the wider programme opportunities as material to how the Pezego evaluation was structured and reviewed.

What this engagement was not

In honest terms: the case study is a third-party profile of Mutus Tech’s participation in a UK innovation programme. It is not a customer pilot, a sales endorsement, or a certified product audit. The Pezego performance numbers come from a structured evaluation under the BridgeAI Scientific Advisor framework — useful as a credibility signal, but not a substitute for a farm-side commercial pilot, which Mutus Tech runs separately on real fields.

Read the original

The original article is published by Innovate UK Business Connect:

• Mutus Tech: A vision to transform agriculture through AI — iuk-business-connect.org.uk · 1 April 2026