AgriSynth is a UK company with a global vision. We create synthetic images used to train AI vision systems for use in agriculture.
Our synthetic image creation engines produce biologically accurate images of complex agricultural crop scenes. They include crop, weed species, pests and diseases on the leaves of the crop, and soil backgrounds with objects like stones.
This is a breakthrough. Currently, training an AI vision system required images collected from the real world, using a camera, season after season to show all the variables year after year. Even worse, every image must be manually ‘labelled’, like colouring in every object in every image! That way the AI model could learn what each object was.
AgriSynth generates synthetic images on demand, all perfectly labelled.
AgriSynth is a small startup, but we’re talking to some big people!
£250,000
£50,000
£10,000
Join our community to view the full investment opportunity.
Already have an account?
AgriSynth is a UK company with a global vision. We create synthetic images used to train AI vision systems for use in agriculture.
Our synthetic image creation engines produce biologically accurate images of complex agricultural crop scenes. They include crop, weed species, pests and diseases on the leaves of the crop, and soil backgrounds with objects like stones.
This is a breakthrough. Currently, training an AI vision system required images collected from the real world, using a camera, season after season to show all the variables year after year. Even worse, every image must be manually ‘labelled’, like colouring in every object in every image! That way the AI model could learn what each object was.
AgriSynth generates synthetic images on demand, all perfectly labelled.
AgriSynth is a small startup, but we’re talking to some big people!
1.Raised £335,000 with HNWI’s using SEIS and EIS Advance Assurance
2.Won a rare Innovate UK Smart Grant worth £474,000 to solve the major problem of identifying a grass weed in wheat, a problem that costs the UK £400 mill
3.Won two Global Incubator Programs from Innovate UK Edge; one for Canada and a recent second one for Australia, aimed at setting up strategic relationships in those areas
4.European Patent Pending for the software process we use to train AI vision systems
5.5 Proof of Concepts with clients which we plan to lead onto long term commercial contracts
6.Focusing on 4 major verticals in agriculture: robotics, grain, R&D and Vertical Farming, markets that have growth potentials up to 27.3% CAGR
7.Revenue planned for March 2028 based on 150 clients at an annual fee of £220,000 totalling £32 mill (~5-7% of market value)
8.Attractive ROI potential with current valuation at £5 million post money and projected 2028 valuation of 8 to 10 x revenues
AgriSynth, where innovation meets agriculture.
Vision
To change agriculture by using AI vision systems to support productivity in a sustainable manner
Mission
To drive the use of synthetic imagery as the future norm for training AI models in agriculture, helping farmers grow food on a more productive and sustainable basis
Value Proposition
Gain control of training AI models using predictable synthetic images, reducing training from years to weeks and saving significant costs
Enhanced vision systems are a game-changer, enabling many opportunities. They can advance Precision Agriculture, currently stalled at treating only parts of fields. We can now move towards treating individual plants and even parts of plants.
Out image creation engines can create plant scenes as well as objects like disease lesions on plant leaves, water droplet on leaves mimicking the real world but without all of the problems year after year.
AgriSynth, where innovation meets agriculture.
Vision
To change agriculture by using AI vision systems to support productivity in a sustainable manner
Mission
To drive the use of synthetic imagery as the future norm for training AI models in agriculture, helping farmers grow food on a more productive and sustainable basis
Value Proposition
Gain control of training AI models using predictable synthetic images, reducing training from years to weeks and saving significant costs
Enhanced vision systems are a game-changer, enabling many opportunities. They can advance Precision Agriculture, currently stalled at treating only parts of fields. We can now move towards treating individual plants and even parts of plants.
Out image creation engines can create plant scenes as well as objects like disease lesions on plant leaves, water droplet on leaves mimicking the real world but without all of the problems year after year.
230,000 MORE MOUTHS TO FEED EVERY DAY
Current agricultural practices are insufficient to meet this escalating demand for food. We must make agriculture more productive but in a sustainable manner using existing farmland. No more deforestation!
We must propel the dream of Precision Agriculture to its natural conclusion and that’s farming individual plants, not whole fields or even parts of fields.
And to achieve that, we need vision systems trained on vast numbers of synthetic images, covering all real-world scenarios.
In turn, those vision systems will support drones, robots, R&D and all other aspects of agriculture to compliment or even replace human eyes and intellect, farming plants or even leaves.
Currently AI systems are trained on real-world images, painstakingly captured year after year and manually labelled, clumsily and inaccurately. That’s why today, agriculture doesn’t have high quality vision systems.
So, without AgriSynth, we will struggle to feed those people.
Precision Agriculture
A concept introduced around 35 years ago, attempting to increase the resolution at which we make decisions and treat crops. Whilst advances have been made, we have got nowhere near the newer dream of treating individual plants and leaves. Robotic hardware, satellite localisation and treatment methods are not limiting this new dream, but robust AI models for vision systems are.
Vertical Farming
In all its forms, this market is growing rapidly. The tolerance for any pest, disease, disorder or dirt on any leaf is zero, and vision systems will have an increasing role to play.
Labelling companies
Such companies rarely consider agriculture but when they do, we will offer them a solution. Currently they accept real world datasets from customers and label them using basic methods and labour in Asia. The labelling is poor and so therefore are the AI models trained on that data. These companies could pivot to synthetic data and supply trained AI solution with the support of AgriSynth, for any plant or grain-based images.
Augmented Reality
Imaging walking through a crop or down a country lane and having spectacles light up every plant species, pest disease or object. The possibilities here are almost limitless.
Being more attentive to detail in crop production is known to produce dramatic benefits. For example, world records for wheat are 4 times the UK National average yield. It’s that attention to detail that provides the benefits.
Using a vision system trained with synthetic images enables the production of robust AI models in agriculture. Such AI models can ‘see’ and interpret individual plants and further AI models can determine the best individual treatment. The vision system is key and that’s what AgriSynth is delivering.
AgriSynth can help robotics companies (around 300 globally today and increasing), R&D field trials (billions of plots around the world), crop protection product development, grain quality analysis and Vertical Farming, to open doors into new markets, extend their services to a wider range of farmers, and allow those farmers to increase productivity in a sustainable manner.
AgriSynth makes the dream of individual plant and leaf analysis and treatment a reality!
As an emerging technology our mission is to drive the use of synthetic imagery for training AI models.
We will market trained AI models under a licensing revenue model where possible and move to a ‘pay per identification’ revenue model eventually. Alongside that we will offer a subscription approach for clients needing image datasets and in some specific instances enter into a revenue sharing agreement where start-up clients lack cash early in our engagement.
These revenue models are being initiated through paying Proof of Concept engagements. This allows our new clients to gain confidence in the paradigm shift that our new technology offers them.
AgriSynth is focusing on 4 verticals as its target markets. Agricultural Robotics, Agricultural R&D, Grain Quality Control and Vertical Farming. Each of these markets is forecasted to have strong growth over the next 5 years with CAGR ranging from 6.2% to 27.3%.
Current PoC’s that are in the company’s pipeline cover 3 or these 4 markets (Vertical Farming will be engaged in Q3 2024).
Biologist, Agronomist, International Change Manager
Investment Banker, Financial consultant
New breed of AI Engineer
3D development modeller
Top 50 Global Data Visionary
Published international researcher
Investment Banker, Lead Advisor and Mentor
Investment Banker, Financial consultant
Investing in a startup involves risk, including loss of capital, lack of liquidity and dividends, and dilution, and should be done only as a part of a diversified portfolio. Please read our Capital at Risk Warning before investing. Please note that investments should be made by investors who understand and accept these risks, and tax treatment depends on individual circumstances and is subject to change at any time.
TrendScout does not provide legal, financial, tax or investment recommendations, and no communications from TrendScout, through this website or any other medium should be construed as such. Furthermore, nothing on this website shall be considered as an offer to sell or a solicitation of an offer to buy any equity, shares, or security to any person in any jurisdiction to whom or in which such offer, solicitation or sale is illegal.
