Understanding the investment opportunity
Big data solutions for agriculture. Thanks to our technology we can improve strategic decisions that mean an increase of up to 20% of the product value and a cost reduction of up to 40%; all this without the need to install IoT equipment.
Companies in the agricultural sector constantly suffer from commercial, quality, safety, sustainability and product competition pressure.
Weather is one of the factors that has the greatest impact on the efficiency of their agricultural production, but it is not the only one. It is estimated that there are between 10 and 200 objective variables that can be used to make decisions and that all of them have some influence on the ripening and volume of the product obtained.
Decisions regarding harvesting dates and agricultural production are still made in the traditional way, based on subjective forecasts by the people who manage a farm. These forecasts can contain errors of between 10% and 40%, which represents huge losses for these production companies.
In this context, the artificial intelligence and the Big Data of RawData counteract these problems, allowing to take advantage of the innumerable variables and sources of data existing in the sector and in the own exploitations, and objectifying and optimizing the decisions.
RawDatafacilita provides farm managers with a data integration and decision support tool to optimize decisions at three strategic points:
- Harvest planning (optimal date of harvest and expected volume).
- Integration of multiple data sources and data analysis in a single solution.
- Crop health (diseases and/or meteorology).
In this way, by combining agrometeorological databases, satellite images and other data sources with user data, RawData helps the client to make decisions that impact on cost reduction and increase the quality of their products, and therefore, of their profits.
One of the main advantages of this technology is that it operates without the need to implement any type of IoT device in the field to provide the service. The fact that there is no need to install equipment reduces the cost of implementing the service and exponentially increases the scalability of the project.
Finally, and taking advantage of the participation in a demonstration project, RawData launches at the beginning of 2020 a solution to digitalize work reports verifying the identity of the worker with facial recognition.
This solution is addressed to the same target of clients adding the market of the TEA's that operate in the agricultural sector. This service allows to complement the technological offer of RawData
- predominantly saas
Aportando soluciones tecnológicas con Big Data para el sector agro. Con el reto de ayudar a crear una agricultura más sostenible y con menos
David Olmo Pérez
Amplia experiencia en machine learning y deep learning. He trabajado durante los últimos 3 años en Grifols en desarrollo y gestión.
Alejandro Martín Vázquez
Full Stack Developer
Josep Anton Mir
Open Future (Cornellà)
Reasons to invest View more data
According to Forbes, investment in Agritech worldwide has increased fivefold in the last eight years. Agritech is undoubtedly one of the sectors that will grow the most in the next years:
RawData has obtained a CDTI Cervera loan worth 250k in 2019.
We have achieved 25 reference clients with successful results that validate the value contribution, the business model and the scalability.
100% of the clients obtained in 2018 renewed contracts for 2019 and subsequently for 2020.
This is the 2nd startup founded in agrotech by the CEO and the fourth project in which he participates with roles linked to the transfer and the business. In total he has accumulated more than 250 experiences with different agri-food clients where he has promoted the introduction of technological innovations and/or digitalization.
David Olmo, with the role of CTO in RawData, has assumed the leadership of global projects in the field of data science in organizations such as Grifos.
- The founding partners, besides having family ties in agriculture, have knowledge, contacts in the sector and complementarity to carry out both the development and the scalability of these services in a growing sector of these technologies.
This is the optimum time to invest, once the value contribution to customers has been validated with scalable solutions based on data and decision-making technologies.