Companies That Trust Us
Why You Need Our Data Annotation Services for AgTech:
- We have a permanent specialist annotation team, guaranteeing the highest quality of service.
- Our team consists of subject-matter experts, including agronomists, doctors, and LiDAR experts.
- We can scale our services according to your business needs, always functioning at peak efficiency.
- Aya Data has the expertise and experience to annotate data for the most complex and specific AgTech use cases.
- We offer only high-accuracy annotation for computer vision models and precise image and sensor data analysis.
Data Acquisition for AgTech
- Monitor environmental data like humidity, soil moisture, and temperature in real-time to make the correct decisions for your business.
- Utilize our wide network of partners from the agricultural industry to acquire region-specific historical data, from weather patterns to soil conditions.
- Manually collect image, video, and sensor data to train unique ML models.
Data Science and AI for AgTech
- Refine your planting strategies by building predictive machine learning models for your local.
- Optimize the way you detect pests and diseases to provide proper treatment and mitigate the damage before it spreads.
- Train machine learning models based on historical and real-time data to enhance your fertilization, irrigation, and soil management practices.
AgTech Case Studies
Combining Soil Acidity Data with Product Sales to Create Unique Business Intelligence
Demeter, an agricultural inputs supplier that operates in West Africa, specializes in working with smallholder farmers to enhance crop yields using primarily organic fertilizers. In order to optimize their product offers and serve the needs of their customers, Demeter sought to utilize open-source data on soil acidity. This information would be used to gain insights into their target markets and customize product recommendations.
Leveraging Drones and AI to Increase the Efficiency and Decrease Risk in Reforestation Projects
Oko Environmental, a reforestation company dedicated to combating climate change by establishing indigenous forests in West Africa, intended to utilize drones and machine learning solutions to gather valuable data and insights regarding their reforestation projects.
Using AI and Drones to Create Precision Agricultural Systems for Commercial Farming
Managing large-scale commercial farms necessitates a lot of progress tracking and repetitive tasks, in addition to being manually overwhelming. However, crop management systems powered by drone-fed computer vision models are a solution to the traditional system of manual data collection, while improving data accuracy and providing valuable insights into farming operations.
Building a Model to Rapidly Identify Disease in Ghana’s Maize Plants
Maize is one of the most important crops for Ghana’s agricultural industry; there have been significant, largely successful, investments into finding solutions to increase yields over the years. However, maize diseases still pose a significant challenge for maize farmers and communities.
Sourcing and Annotating Large Volumes of Agricultural Imagery for Precision Spraying
Client X is a leading AgTech company focused on improving agricultural productivity and sustainability through cutting-edge technology solutions. Their aim was to have their in-house data science team develop a computer vision model that would detect and identify weeds.
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