TensoAI uses proprietary AI models to extrapolate data from external sources such as Weather Stations and Satellite Imagery sources. Correlating your farm information allows us to predict the quantity and quality metrics, such as Acid and Sugar level, that are important to drive decisions with supply chain challenges.
For some farms, we use a Federated Learning Technology that aids in augmenting the accuracy of our models without risking data security. We utilize privacy-preserving tools to ensure that all data-ownership rules are adhered to and your data is always safe.
We understand the challenges of growing crops. Our goal is to provide insight and knowledge about your farm, with the least amount of resources. All we need from you are:
Soil Test results, Farm Boundary, and Harvest Information.
We handle the rest.
We generate the following 3 reports for you through the growing season:
01
Pre-Vegetation Analysis
Much of the heavy lifting comes from setting up the framework to perform analytics. Data Collection is an integral step in providing analytics in future reports. Data such as Soil Tests, Weather Station, Satellite Imagery, and Historical Data is gathered in this step.
A Pre-Vegetation Analysis is performed to understand parameters such as: Field Capacity, Soil Composition, Rainfall accumulation, Solar Radiation and past harvest yields.
02
Weekly Analysis Reports
Being part of the growing season is how we understand the complexities of fruit production, and the parameters important in the manufacturing process. We extend the original report to include such information as, Precision Irrigation Schedule, Soil Moisture Hotspots, NDVI coverage, Yield Insights, and Quality Metrics.
03
Quality and Quantity Forecasting
Utilizing historical data, we train our AI models to deliver predictive information on Quality and Quantity metrics before harvest time. Our AI uses a proprietary model that injests data established in the previous steps. Access Information such as, Harvest Time Prediction, and Quality/Quantity forecasting.
Let Us Digitize Your Vineyard
Predict Harvest Metrics
Harvesting is a stressful time, and having mission-critical data helps in making time-dependent decisions for your crop. Predicting Quality and Quantity metrics such as Yield, Sugar and Acid levels that drive revenue will greatly allow farms to navigate upcoming supply chain issues.
Predictive data leads to predictive scheduling, which are seen to have 5% increase in Productivity and 8% increase in Employee Retention.
Soil Moisture Hotspots
Soil is the lifeblood of your crops. Soil health and its moisture content controls the availability of water to your crops. Nutrients are also trapped without adequate moisture, and results in negative growth. Some of these Hotspots are rarely seen until its too late, and can easily be remedied through early detection.
Our AI model are able to penetrate through cover crops to attain soil moisture data at 10m resolution.
Irrigation Scheduling
Water availability is a vital metric in creating algorithms around crop growth. Irrigation Scheduling according to predictive weather, soil capacity, quantity and quality metrics is important in future harvesting predictions.
Our Irrigation module can be used in 2 modes: Minimal Water-use (reduce crop loss), Maximize Harvest (Optimize Quality or Quantity metrics).
No Expensive Hardware Required
Here at TensoAI, we know all hardware is expensive. We focus on delivering value on data already accessible via Weather Stations, Sattelite, Goverments and Public Organizations. If more data is needed for your farm, we recommend multiple hardware suppliers for a low-cost solution to data capture.
Global Satellites Data
Satellite imagery is used to extrapolate data such as NVDI and Soil Moisture information. This data is vital in both our Algorithm and Model development modules, while being able to ingest multiple sources of satellite imagery (Mondis, Sentinel-1, and Sentinel-2) to accommodate for when cloud cover is below 20%.
Crop Cover is a common obstruction when utilizing satellite imagery as a datasource in soil moisture readings. Our proprietary AI models are able to penetrate crop cover to understand the soil underneath.
Integrating Systems
Here at TensoAI, we believe in integrating existing systems already in place. We work with major software platforms to bring added value to the customer with the least hassle possible.
Our Federated Learning Technology (Seed Network) allows integration into major databases through privacy-perserving tools. Data Privacy is at the center of this technology, and has allowed for numerous models to be built upon already.
How we do it
01. Data Collection
Satellite, Weather Station, Soil Test, Historical data collected onto one platform
02. Data Analysis
Soil Moisture, Rainfall, Field Capacity, Solar Radiation, Environmental paramaters, NDVI per growth stage comparison per season
03. Algorithm Insights
Irrigation Scheduling based on Predictive Weather and Soil Moisture data
04. Predictive Models
Forecast Quantity and Quality metrics according to predictive weather and irrigation scheduling.
Family-Farm
for < 10 Hectares- Federated Learning AI
- Combined Weekly Knowledge Team Reports
- 1 Year Historical Yield data needed
Enterprise Farm
>11 Hectares- Proprietary Cloud AI
- Dedicated Knowledge Team Meetings
- 3 Year Historical Yield data needed
Let's talk
Data digitization and AI models has never been closer