AgNext Technologies, an Agri Food Supply Chain tech startup based out of Mohali, Chandigarh was founded by Taranjeet Singh Bhamra, the CEO of AgNext in the year 2016. AgNext was selected as being one of the best performing agritech companies in Asia by the Dutch-based Rabobank financial services provider in the year 2019 that was followed by its winning of the Best Indian Agritech Start-up Award for the year 2020. Recently, AgNext was presented with the “Most Innovative Agri Startup Award’ at the FICCI Summit and Awards for Innovations by Agri Startups.
In an exclusive interaction, Subrat Kumar Panda, CTO of AgNext Technologies Pvt. Ltd. spoke to Claus from Food Infotech, wherein, he discussed at length about AgNext and its role in developing path breaking technological solutions using Artificial Intelligence that can assess the quality and safety for a range of agri-commodities such as milk, tea, animal feed, spices and grains within a matter of just 30 seconds, thereby helping address the challenges faced by the farmers in obtaining accurate prices for their produce, which will further incentivize them to follow farm practices that can help generate crops of superior quality and a lot more.
Edited Excerpts Below:
1. Firstly, we want to thank you for sparing some of your valuable time for us! Would you describe for us in brief about AgNext and what role it plays in solving the various challenges faced by the Food and Beverages Industry in general?
With a vision to infuse cutting-edge technologies in the unexplored arena of agri- businesses, AgNext was founded in the year 2016. The vision was to focus on rapid improvements in quality, food safety and traceability solutions. The basic edifice in this evolution of AgNext was to increase transparency with effective procurement practices that can help to maintain the quality of food in agribusinesses, apart from helping benefit various stakeholders all along the way. AgNext is today determined to solve issues connected to Food Quality, Food Safety and Food Traceability in agriculture, including the entire food value chain. We have been using the latest data driven technologies that are merged with Artificial Intelligence for instant quality analysis, whether it is physical, chemical or ambient quality of food that can be traced back to its source.
Therefore, using the power AI, we are building trust, speed and transparency between buyer & seller for every transaction across the agriculture value chain. With the right technology in place, farmers can obtain accurate prices for their produce, in addition to having a greater incentive to improve their farm practices for generating crops of better quality. For businesses, this technology helps save money and increase profitability, as now they know what they’re actually paying for. Finally, for consumers, we ensure quality by accurately ascertaining whether there are adulterants or not.
2. AgNext has been working towards implementing data driven technologies. How many varieties of food have you been able to cover with the help of your technologies today?
AgNext has innovated on an AI-based rapid quality assessment solution Qualix, which can instantly assess the quality of commodities & build traceability. It’s just like an MRI for food with the ability to do instant on-field analysis for Grains, Spices & Aromatics, Beverages (Tea, milk) & Animal feed in less than 30 seconds. Qualix analyzes every aspect of food, i.e. physical, chemical and ambient using computer vision, spectroscopy, and IoT-based technologies for food quality monitoring.
3. You have brought in new technological solutions using IoT and AI that has the capacity to analyze or assess the quality of produce in just about 30 seconds or so. Tell us something more about the same?
The effectiveness of our platform lies in the fact that a test result associated with food quality and safety in the agricultural value chain which conventionally is obtainable between 4- 15 days is mostly being made available within 30 seconds through our platform & that too on-field, as the devices are portable and hence reducing the turnaround time. With no associated maintenance cost and zero additional expenditure, our platform also facilitates in cost-saving as it is done through portable and wireless battery-operated devices. So with no or minimal human involvement, the process gets totally digitized removing any kind of subjectivity whatsoever.
4. Please describe a little about any one or two solutions that you’ve offered recently and what they do to solve the challenges faced in the food value chain?
Currently, AgNext has been working as a category innovator in itself, providing a technology platform called Qualix for rapid commodity assessment solutions across procurement, trade, production, storage and consumption of food and agri value chains. The Qualix AI engine uses spectral molecular analysis, computer vision and IoT Sensing solutions delivered through an integrated hardware and software interface for accurate and instant quality analysis along with farmer-wise data for quality produce, managing suppliers by lots and building business intelligence through quality maps. Leveraging on this, AgNext has also been introducing a stream of other SaaS based solutions on its Qualix platform which is expected to benefit its clients for integrating more technology solutions for their benefits. AgNext’s hardware solution suite comprises of devices utilizing NIR Spectroscopy & AI-based image processing technologies.
AI-Based Molecular Analysis – AgNext is one of the companies that has been able to innovate and integrate portable, on field devices connected with its platform, that help in instant molecular analysis of agri commodities in the form of liquids, solids, powders, grains or leaves, pretty much covering the whole spectrum that nature offers.
AI-Based Image Analytics – AgNext has built devices which work with on-premise embedded cameras for instant quality assessment using computer vision sciences. Across India, the majority of crops are assessed manually and with the naked eye, leaving room for multiple inconsistencies, manual fatigue and manipulations, leading to losses across agriculture value chains. This solution removes subjectivity, digitizes transactions and encompasses traceability, all the while consistently being able to provide an accuracy rate of more than 99% delivered at a fraction of the cost and time to stakeholders.
AI-based Sensor Analytics – AgNext pioneered the first applications for LoRA WAN based IOT applications in India, which provide quality estimations in multiple agricultural processes in spatial arrangements, like curing, food storage, warehousing and logistics. AgNext has built STQC calibrated sensors for temperature, humidity, gaseous emissions and other parameters as the key for various agricultural industries such as curing solutions, grain silos, warehouses, food processors and storage services. These provide real-time alerts on control parameters and data analytics for actions to be taken as devized by the research institutions for better management of food quality.
5. Can you describe to us how you manage to detect if a product is about to lose its quality, especially when your products have to pass through warehouses or cold storages before they are released into the open market?
Our technology is focused to infuse innovation in the manner in which operations associated with grains, spices, herbs and beverages are undertaken. For instance, in the case of Milk, our technology has the potential to discern nature, i.e. it’s constitution and the extent of adulteration. For Spices, the intrinsic content value can be found out within a jiffy and while in case of Turmeric, the ability to discern Curcumin has the potential to change the market dynamics of Turmeric.
AgNext’s hardware suite comprises of devices that utilize NIR Spectroscopy & AI-based image processing technologies. The NIR Spectrometers assess the chemical quality assaying of agri-commodities, while AI-based image processing technologies is for physical quality assessment of agri-commodities.
AgNext has pioneered the first applications for LoRaWAN based IoT applications, which provide quality estimations in multiple agricultural processes in spatial arrangements such as curing, food storage, warehousing and logistics. We have built STQC calibrated sensors for temperature, humidity, gaseous emissions and other parameters as the key for various agriculture industries such as curing solutions, grain silos, warehouses, food processors and storage services. These provide real-time alerts on control parameters and data analytics for actions to be taken as devized by the research institutions for better management of food quality. New applications through IoT will enable agribusinesses to increase operational efficiency, lower costs, reduce waste, procure quality produce and reduce loss on trade.
6. If you can explain to us a little more on the technologies that have been embedded inside the solutions you have been offering and how it is able to detect if a product is filled with adulterants or not?
Our suite of technology incorporates AI algorithms on hardware that help us to determine on the basis of various parameters with accuracy. Physical & chemical quality is being checked using computer vision & molecular sciences respectively. We train our AI algorithms in our own R&D labs by building chemical compositions using different types of samples & then extract data out of it to build models. After collecting millions of data points and applying multiple data science algorithms, we are able to train our AI, which is able to detect if any product is filled with adulterants or not.
7. Would you be able to tell us who has been your target audience as of today?
Billions worth of food move across the commodity value chains from production to storage and subsequently to trade, processing and finally for consumption. Each node has applications for our technology that can solve the various issues that are connected to maintaining the quality. Our target markets till date vary sector wise. Our technology covers Milk Dairy processing companies, Public bodies, Milk cooperatives etc. Additionally, it covers Tea processing companies, Tea merchants as well as Spices processing companies, Spices merchants, Nutraceuticals, a few farmer groups, etc. We also cover other segments that include companies that are engaged in grains and millers processing, including warehouses, public bodies, etc. In the case of Animal feed, we have been able to cover a few manufacturing companies, public bodies, etc.
8. Do you feel there is any specific segment or section of the industry that is largely unaware about any specific solution or solutions that you offer today for the businesses that deal in various types of food and agro-products?
As for the segments that we feel are still unaware, we have been focusing our efforts by targeting a few Farmer Producer Organizations (FPOs) and are trying to enlighten them about the advantages of adopting our advanced technology that can help them make cost-effective and cost efficient trading decisions.
9. Can you share a bit about any specific hardware of yours that is being used to offer solutions such as assessing food commodities and so on and why you consider it to be unique?
Our SPECX series is an NIR based rapid non-destructive chemical quality assessment technology which determines the various parameters for assessing protein, moisture, oil, gluten, starch, ash content etc. that is present in commodities such as wheat, paddy, barley, soybean, mustard, maize, animal feed & other grains within a short time period of just 30 seconds.
Owing to its portable feature, one can carry & use it anywhere on-field. It comes in two variants. The first is the SpecX Max which is a handheld device capable of testing samples comprising of about 20-30 grams at a time and weighs approximately just one kilogram. SpecxPro is a tabletop device capable of testing samples comprising of about 250-300 grams. It weighs approx. 7 kilos and is recommended for warehouses and collection centers. Moreover, both the devices come with a touch interface giving instant results with easy ERP integration.
10. Could you let us know something about AgNext’s revenue models as on date?
The revenue model of AgNext comprises of a SaaS based subscription of the solutions that it has been offering, wherein, hardware and software are provided as a service to companies. This subscription based service is being deployed currently both on an annual basis as well as rental basis of per month subscription.
11. According to you, which are all the areas where your various tech solutions are anticipated to find their application in the entire food supply chain network?
Our technology sits at every buyer seller intersection in the agriculture value chain, especially at collection centers, warehouses, food processing centers, traders and the likes.
12. How many countries in the international market have you been able to reach out to with your various technological solutions?
We have been able to reach out to a few countries, particularly some of the neighbouring Southeast Asian countries. In the future, we are also looking to expand our presence in many other regions such as Europe, Africa, parts of West Asia, particularly the Middle Eastern nations as well as the markets in North America, particularly the United States.
13. Lastly, if you could let us know what’s currently in the pipeline for AgNext in 2021 or in the immediate future?
Our mission is that 5% of the global food should move through our platform in the next 5 years to ensure food safety, sustainability and traceability. In future, we would be building a team on Quality based Trade, wherein, all of these services would be brought under a single platform solution to ensure a Fair Trade and Direct from Farmer-to-Consumer opportunity. Our future plans are to try and develop as much of such IPs, patents that can cover several other commodities and also to reach out to all the major food processors as well and provide them with a solution that not only would be able to ease the supply of quality food for billions in India, but also right across the world.