Dpoll-Digital Pollination
Agrifood sector needs a RADICAL transformation of food systems to move towards more resilient and sustainable systems. As a root of the pyramid is farmer’s capacity building, There is large no of organisations, farmer groups, financial Institutes, individual farmer, Govt and private sectors etc involved in the farmers benefit.The survey shows the collection & process of data and Filter of useful data is consuming almost 40% of the resources of organisations with nearly duplicate data. Technology solution TeamFarm assists such organisations to be always equipped with intelligence to focus make decisions, design strategies, intelligence for policymaking to empower farmers and Agri-food sector, rather investing in efforts.
We focus Crop GeoData platform building for inclusive agroecosystems for economically viable options and ecologically sustainable actions for more food, nutrition and health which is essential to achieve SDG2.0
This practice will surely help in doubling the farmers' income which is Prime minister's vision.
Farmers Capacity building organisations like Govt, NGOs, Farmer companies, Financial-Insurance Institutes need real-time Land-Crop discovery, huge-scale data & with intelligent analysis for their strategic research, preparedness & response continuous program for policymaking, action plan etc. The availability & accessibility of such processed farm-level crop data is the problem.
According to the world bank, India has a total area under cultivation is 179 million hectors where almost 65% population engaged direct & indirect way in agriculture. These people are the ultimate beneficiaries of the solution.
Consider the geographical area of the country like India, It’s quite tedious and hard to reach each n every field and collect the information and generate insights by traditional ways. And process these iterations continuously. But now with the support of improved technology infrastructure like Satellite data, high-speed internet, development of Artificial Intelligence and revolutionary smart mobiles we are towards to overcome this.
Support organisations with smart analysed land-Crop discovery by large area monitoring in terms of crop suitability mapping, production data & prediction, real-time info, early warning signals with our remote sensing mechanism.
Availability of farm-level data is a big issue to enrich their work and make a more effective impact on the ground.To introduce strategies, policies and planning for better capacity building in Ag you need more accurate, iterative, real-time field-level data and analytical insights.
Our GeoData platform solution is based on Farm to pixel and Pixel to Farm mechanism & access of such a analysed data more easily, application and user friendly is a the hurdle.
We focuson very broad rage of users from individual farmer, Farmer groups, private sectors, NGo's to Govt. In Single line every head who works in capacity building of the farmers is our user. And ultimately Farmers and agrifood sector are the beneficiaries.
The ICT-mobile technology is the answer to engage them also reading the needs and provide the solution.
We definitely believe that the correlation in the long-term benefits is increased in Farmer's resilience by capital access & synergies in farm decision practices, as well as decreased expulsion and suspension rates, and then also ultimately increased in sustainable food production. We do believe that this is applicable outside of India. We actually plan to have associate partners in Central and South Africa.
- Support small-scale producers with access to inputs, capital, and knowledge to improve yields while sustaining productivity of land and seas
Intelligent, proper & right time Inputs leads the efforts to make more impacts.Similarly out solution helps to improve agri sector by various ways.
Our insight is input for Organisations, farmers etc they utilise those intelligence to their mechanism and at the end we found impact on the field and agri-production & livelyhood.
- Prototype: A venture or organization building and testing its product, service, or business model
- A new application of an existing technology
We can say Planet.com, EOS and couple of Satellite data providers are the competitors. But our core USP is compilation of Crop Profiling and Land-crop discovery.
With our AI; the crop model can easily replicated to other farm land around the globe and organisation doesn't need to invent the wheel, rather enhancing the work of capacity building.
It's a combination of Satellite imaginary GeoData, ML-AI and fieldlevel Crop domain knowledge acquisition system, Web API's & mobile App .
We are associating with a Table Grape oriented application Grape Mundo to piloting our solution. With 14000 farmers we get very good sample size. Currently co-creation and sharing of the knowledge is going on. Resulted we got feed back from couple of selected farmers that they are improving water management by geodata insights and understanding other farmers practices.Also there is declination of farming expenses.
- Artificial Intelligence / Machine Learning
- GIS and Geospatial Technology
- Imaging and Sensor Technology
- Software and Mobile Applications
- Women & Girls
- Rural
- Peri-Urban
- Poor
- Low-Income
- 2. Zero Hunger
- 12. Responsible Consumption and Production
- 17. Partnerships for the Goals
- India
- India
- South Africa
Currently 14000 Farmers and 4 Organisations are using it.
By the next year we will reach to 150000 farmers and 100 organisation as we have been contacted by producer companies, farmer groups and educational institute officials to implement and validate the project.
The way we've been thinking about scaling our platform is, first we would love to work with more partners—NGO’s, FPOs, farmer groups or Educational Institutes, farmer, to first broaden our user base and then gather more data with them.
Parallelly, We focus on adding crop profiles. At Initial 1st yr we serve Grape Farmers which spared vineyards over 1,50,000 hectors in our state. Our scaling plan is increasing in cultivated land acreage under the profiled crops this will helps us in reduce the cost of technology conversion, analysis and make continuous accessibility to the farmers. When talking about business model we adopt a hybrid model of horizontal and vertical approaches at the stage we look for funds as to make sure tools will be more effective and always free for the farmers then we will reach govt, NGO and exporters for earning and make this model self-sustainable.Our revenue model will be Data usage and special purpose applications.
Funds is the major hurdle for us, without that we can not engage more talent to our team.
Fund raising through grants and technology partnership extension.
And the team can help to overcome technological limitation.
- For-profit, including B-Corp or similar models
Full time 5 , part time 2 consultant 3 and more that 50 volunteer farmers/domain experts.
Our team has very good combination ground level knowledge persons, AI/Ml & mobile technology experts and very experienced advisory. We have adopt bottom up approach so we understand the need and working towards it.
Currently we two groups of farmers for Ground Level domain expertise:
- Indigenous Farmers Producer
- Grape Mundo farmer groups
Technological Partnership
- Microsoft : We got the Grant $10,000 for out project Ai4Earth challenge.We got Azure resource support and technical guidance.It's time limited but we will look for extension.
- Grape Mundo : For Ready Mobile App integration for existing solutions
- Organizations (B2B)
Expenses are increases with our boundaries expands. More land under our platform more expenditure .At initial stage to capture historical, current geodata & build AI crop model we need grant.I found MIT solve always nourish future tech and can sense benefits of the technology in ag sector.
It is the primary reason to apply to solve.
- Funding and revenue model
- Talent recruitment
- Board members or advisors
We are approaching Microsoft for extending the partnership which we utilize for cloud infra.
Refugee Farming is increasing and it's equally important to satisfy the nutritional needs and improve livelyhood. Our solution can help the organisation which works in refugee areas. With little efforts, they can raise the capacity of the farmers in that region.
Crop Profiling is geographically centric process but when we have huge data set of Crop-Land, weather, soil moisture, local farmer knowledge and other factors. One can replicate the AI model of crop profiling which is more disease and climate resilient.
So when fighting with hunger it's really futuristic to have such a AL model which tells what is current growing stat, predictive analysis of production and where this crop model can be replicate etc.

Director