To say agriculture is one of Sri Lanka’s lifeblood industries is an understatement. We were all famously told in school that back in the (ancient) day, Sri Lanka used to be called the “Granary of the East”. Kings of old made their mark by building mammoth tanks or manmade lakes that, apart from being picturesque, primarily provided irrigation for farming. The timing of the Sinhala and Tamil New Year also marks the end of the harvest season.
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Jeevan Gnanam and Mike Richardson[/caption]
Most of our biggest industries include agriculture; tea, rubber, coconut, and tobacco industries – they all depend on farming. While the information age has affected many industries, agricultural industries have not been affected as much, at least not in the way they physically do things. Until now. Meet SpectrifyAI, the artificial intelligence (AI) spectral scanner that is set to transform Sri Lankan agriculture.
A part of VeracityAI, Sri Lanka’s fastest-growing AI company, SpectrifyAI is a new suite of solutions specifically designed to radically optimise production, agri-inputs, and quality control across the entire value chain for tea, spices, and herbs for the first time in Sri Lanka.
Leveraging the very latest advancements in spectral scanning, AI, and machine learning, SpectrifyAI delivers end-to-end consistency on quality standards directly into the hands of producers and value chain partners. This is accomplished by deploying extremely low-cost patented spectral scanners paired with AI to conduct real-time spectral analyses of everything – from soil composition to the chemical makeup of tea, spices, and herbs at every point, from field to factory to the final buyer.
SpectrifyAI’s capabilities can also be merged with VeracityAI to analyse satellite imaging of land to track harvest development and study historical data to predict yields and risks. Additionally, SpectrifyAI also offers integration with GoMicro, another groundbreaking AI detection tool that converts any smart device with a camera into a powerful handheld microscope for instant analysis and identification of plant pests and diseases.
The people behind this latest agricultural innovation are Jeevan Gnanam and Mike Richardson.
Serial entrepreneur Gnanam needs no real introduction. While serving as Chief Executive of St. Anthony’s Industries, Gnanam founded and grew Sri Lanka’s largest IT park Orion City as well as incubator and accelerator Hatchworks, among several other ventures including SA Knowledge Services (SAKS) and VeracityAI which he founded in 2017. Gnanam also helped write and shape the country’s AI Policy Framework.
Richardson is one of the leading experts for agile development in photonics. He has over 15 years of experience in the field and has close ties to the German research organisation Fraunhofer Gesellschaft.
We caught up with Gnanam for a brief chat on SpectrifyAI and what it can mean for agriculture.
Following are excerpts of the interview.
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SpectrifyAI tells about the chemical composition of any organic material[/caption]
What sparked the idea behind SpectrifyAI? How does it work?
I was trying to solve getting data on levels of nitrogen, phosphorus, and potassium (or NPK levels) in the soil for a particular party. Because of my fascination for astronomy (I watch a lot of documentaries on the subject), I knew how we studied chemical compositions of planets and wanted to see if we could do the same thing for soil. I was intrigued by whether such a device existed, looked around, and that was when, through a mutual friend, I met Mike, who was working on blended teas. The rest, as they say, is history.
Mixing agriculture and AI – how does this happen?
Artificial intelligence and machine learning just replicate and deliver consistently the best of aggregated human expertise. This in turn can be used to automate a lot of problems for agriculture. It’s now one of our main focus areas. In SpectrifyAI, we leverage AI’s consistency to understand quality in tea using spectroscopy.
So far, SpectrifyAI has only been applied to the tea industry. Does it work for other industries and how?
Actually, SpectrifyAI fundamentally can tell you something about the chemical composition of any organic material. This could work for a number of different industries. For example, we are having some good results in the fish exports industry to help understand histamine content, but this can work for a number of industries like cinnamon, spices, herbs, etc.
How does SpectrifyAI maximise tea production?
We want to lift the entire tea industry in Sri Lanka. As a nation, we are stuck at about Rs. 1.5 to Rs. 1.8 billion in annual revenue, with approximately 300,000 tonnes annually. With SpectrifyAI, we can assure quality and give details such as caffeine levels, taste profile, sugar content, moisture content, etc. to potential buyers. Buyers are going to pay more for something they know chemically and can test when they receive to be spectrally similar.
How can SpectrifyAI solve bigger agricultural problems?
By solving for quality across the supply chain, we believe we can help uplift the lives of farmers. This is important, as most farmers have irregular incomes and live a hand-to-mouth existence.
What is SpectrifyAI’s big future vision?
Apart from enabling and uplifting supply chains and farmers in Sri Lanka, we want to prove that this Sri Lankan product/service can scale globally. We have some interest in markets like Thailand and Indonesia which could be quite exciting for us.
What happens to the human aspect of agriculture? How does it need to evolve to adapt to AI like SpectrifyAI?
Humans should not be doing repetitive tasks, especially manual tasks. Whether it’s understanding quality, to manual work in the field, humans should use the best tools to get the job done effectively. We believe farmers will identify and understand the need to adopt technology to improve their livelihoods, mainly because in the past they have already been doing so with tools like tractors, fertilisers, etc. We are just another tool for them.
Jeevan Gnanam and Mike Richardson[/caption]
Most of our biggest industries include agriculture; tea, rubber, coconut, and tobacco industries – they all depend on farming. While the information age has affected many industries, agricultural industries have not been affected as much, at least not in the way they physically do things. Until now. Meet SpectrifyAI, the artificial intelligence (AI) spectral scanner that is set to transform Sri Lankan agriculture.
A part of VeracityAI, Sri Lanka’s fastest-growing AI company, SpectrifyAI is a new suite of solutions specifically designed to radically optimise production, agri-inputs, and quality control across the entire value chain for tea, spices, and herbs for the first time in Sri Lanka.
Leveraging the very latest advancements in spectral scanning, AI, and machine learning, SpectrifyAI delivers end-to-end consistency on quality standards directly into the hands of producers and value chain partners. This is accomplished by deploying extremely low-cost patented spectral scanners paired with AI to conduct real-time spectral analyses of everything – from soil composition to the chemical makeup of tea, spices, and herbs at every point, from field to factory to the final buyer.
SpectrifyAI’s capabilities can also be merged with VeracityAI to analyse satellite imaging of land to track harvest development and study historical data to predict yields and risks. Additionally, SpectrifyAI also offers integration with GoMicro, another groundbreaking AI detection tool that converts any smart device with a camera into a powerful handheld microscope for instant analysis and identification of plant pests and diseases.
The people behind this latest agricultural innovation are Jeevan Gnanam and Mike Richardson.
Serial entrepreneur Gnanam needs no real introduction. While serving as Chief Executive of St. Anthony’s Industries, Gnanam founded and grew Sri Lanka’s largest IT park Orion City as well as incubator and accelerator Hatchworks, among several other ventures including SA Knowledge Services (SAKS) and VeracityAI which he founded in 2017. Gnanam also helped write and shape the country’s AI Policy Framework.
Richardson is one of the leading experts for agile development in photonics. He has over 15 years of experience in the field and has close ties to the German research organisation Fraunhofer Gesellschaft.
We caught up with Gnanam for a brief chat on SpectrifyAI and what it can mean for agriculture.
Following are excerpts of the interview.
[caption id="attachment_121925" align="alignleft" width="365"] SpectrifyAI tells about the chemical composition of any organic material[/caption]
What sparked the idea behind SpectrifyAI? How does it work?
I was trying to solve getting data on levels of nitrogen, phosphorus, and potassium (or NPK levels) in the soil for a particular party. Because of my fascination for astronomy (I watch a lot of documentaries on the subject), I knew how we studied chemical compositions of planets and wanted to see if we could do the same thing for soil. I was intrigued by whether such a device existed, looked around, and that was when, through a mutual friend, I met Mike, who was working on blended teas. The rest, as they say, is history.
Mixing agriculture and AI – how does this happen?
Artificial intelligence and machine learning just replicate and deliver consistently the best of aggregated human expertise. This in turn can be used to automate a lot of problems for agriculture. It’s now one of our main focus areas. In SpectrifyAI, we leverage AI’s consistency to understand quality in tea using spectroscopy.
So far, SpectrifyAI has only been applied to the tea industry. Does it work for other industries and how?
Actually, SpectrifyAI fundamentally can tell you something about the chemical composition of any organic material. This could work for a number of different industries. For example, we are having some good results in the fish exports industry to help understand histamine content, but this can work for a number of industries like cinnamon, spices, herbs, etc.
How does SpectrifyAI maximise tea production?
We want to lift the entire tea industry in Sri Lanka. As a nation, we are stuck at about Rs. 1.5 to Rs. 1.8 billion in annual revenue, with approximately 300,000 tonnes annually. With SpectrifyAI, we can assure quality and give details such as caffeine levels, taste profile, sugar content, moisture content, etc. to potential buyers. Buyers are going to pay more for something they know chemically and can test when they receive to be spectrally similar.
How can SpectrifyAI solve bigger agricultural problems?
By solving for quality across the supply chain, we believe we can help uplift the lives of farmers. This is important, as most farmers have irregular incomes and live a hand-to-mouth existence.
What is SpectrifyAI’s big future vision?
Apart from enabling and uplifting supply chains and farmers in Sri Lanka, we want to prove that this Sri Lankan product/service can scale globally. We have some interest in markets like Thailand and Indonesia which could be quite exciting for us.
What happens to the human aspect of agriculture? How does it need to evolve to adapt to AI like SpectrifyAI?
Humans should not be doing repetitive tasks, especially manual tasks. Whether it’s understanding quality, to manual work in the field, humans should use the best tools to get the job done effectively. We believe farmers will identify and understand the need to adopt technology to improve their livelihoods, mainly because in the past they have already been doing so with tools like tractors, fertilisers, etc. We are just another tool for them.