Supporting AI-Driven Innovation in Robotics
Aya Data helps clients drive the evolution of robotics with a full spectrum of services, including robotic vision annotation, data acquisition, and end-to-end model development. By combining real-world and synthetic data, we train robots to effectively navigate and perform in complex real-world conditions. We aim to support the development of advanced, perceptive robots that not only move but truly understand and adapt to their environments.
Our Clients
Accelerating Robotics Development with AI
We offer specialised AI services for robotics, including precise vision annotation, data acquisition from sensors and simulations, and end-to-end AI model development. Our team collaborates with you to address key challenges, such as improving autonomous navigation, refining robotic manipulation, and optimising environmental interactions.
Data Annotation
Our expert team enhances robotic perception through precise visual data labelling. From annotating 2D images for object detection to labelling 3D point clouds for scene understanding, we ensure your robots have the high-quality training data they need to navigate and interact with complex environments.
Data Acquisition
We collect data from multiple sources – sensors, cameras, and other robotics hardware – to provide valuable, relevant data for AI robotics projects. We can also deploy simulation tools to generate high-fidelity synthetic data that closely mimic real-world scenarios, enabling you to train and test models in non-destructive, cost-effective environments.
AI Consulting
Our experienced robotics engineers and AI experts work closely with you to develop custom solutions that address your specific challenges. From autonomous navigation and manipulation to robot-human interaction, we help you harness the power of AI to create intelligent, adaptive robotic systems that excel in the real world.
Why Use Aya for Your Healthcare Project?
-
-
Exceptional Customer EXPERIENCE
- 1. Clear, timely project communication
- 2. Value-focused robotics engagement
- 3. Flexible timeframes for efficient delivery
- 4. Transparent pricing and policies
- 5. Dedicated robotics project support team
-
-
-
Unwavering QUALITY
- 1. Custom robotics quality control measures
- 2. Innovative solutions for complex data
- 3. Swift issue resolution processes
- 4. Rigorous multi-step verification process
- 5. ISO, GDPR, SOC2 compliant standards
-
-
-
Unparalleled EXPERTISE
- 1. Specialised robotics domain knowledge
- 2. Broad external expert partnership network
- 3. Cutting-edge robotics AI implementation
- 4. Continuous robotics AI skill development
- 5. Proven track record of robotics success
-
Case Study
Leveraging Drones and AI to Increase the Efficiency and Decrease Risk in Reforestation Projects
Oko Environmental, a reforestation company, sought to use drones and machine learning to gather comprehensive data on their projects, covering germination rates, tree growth, environmental changes, and potential risks. The AI model, trained on drone data, provided impactful insights, increasing germination rates from 72% to 94%. This improvement enhanced decision-making and boosted project efficiency through streamlined data collection and automated analysis.
Combining Soil Acidity Data with Product Sales to Create Unique Business Intelligence
Common maize diseases were often misdiagnosed and mistreated in rural areas of Ghana, which Demeter Group sought to address. With the help of agronomic experts in Ghana, Aya Data labelled 5,000 images captured with smartphones. Using this labelled dataset, Aya Data trained an Artificial Neural Network (ANN) that displayed an impressive 96% accuracy in identifying disease types and severity levels in maize plants from the images.
Combining Soil Acidity Data with Product Sales to Create Unique Business Intelligence
Common maize diseases were often misdiagnosed and mistreated in rural areas of Ghana, which Demeter Group sought to address. With the help of agronomic experts in Ghana, Aya Data labelled 5,000 images captured with smartphones. Using this labelled dataset, Aya Data trained an Artificial Neural Network (ANN) that displayed an impressive 96% accuracy in identifying disease types and severity levels in maize plants from the images.