FAQs
Find answers to common questions about our AI services and products, and how you can work with Aya Data to implement your AI solutions.
Common Questions
Data Annotation
What types of data annotation services does Aya Data offer?
Aya Data provides a comprehensive suite of data annotation services tailored to diverse AI needs. Our expertise spans image and video labelling, including advanced techniques like instance segmentation and 3D point cloud annotation. In natural language processing, we cover everything from named entity recognition to sentiment analysis and specialised tasks like legal document annotation.
How does Aya Data ensure the quality of its data annotation?
We maintain quality through AI and expert reviews, regular annotator training, and real-time process updates based on project metrics.
Can Aya Data handle complex or specialised annotation projects?
We excel at complex annotation, assembling specialized teams and adapting tools for unique projects. Our collaborative, iterative approach ensures high-quality output, and we have a proven track record in diverse fields like medical imaging, NLP for African languages, and autonomous vehicle systems.
What sets Aya Data's annotation services apart from competitors?
At Aya Data, we use a combination of skilled annotation experts and advanced AI tools to ensure the highest level of accuracy. All annotations are reviewed by qualified professionals to meet strict industry standards (ISO).
What are data annotation services?
Data annotation services involve labeling raw data, such as images, videos, text or audio, to make it machine-readable for training AI and machine learning models. High-quality annotations ensure accurate predictions and smarter AI systems.
Why are data annotation services important for AI and machine learning?
Accurate data annotation is essential for training AI models to recognize patterns, classify data and make predictions. It helps ensure that AI-powered systems deliver precise and reliable results across all industries. Aya Data is able to annotate images, text, audio and video. Our comprehensive annotation services include:
A. Computer vision annotation: Bounding boxes, polygon annotation, image segmentation, keypoint annotation
B. Natural language annotation: Named entity recognition (NER), sentiment analysis, audio/text translation, Reinforcement Learning from Human Feedback (RLHF)
C. 3D annotation: 3D bounding boxes, 3D polygon annotation, 3D semantic segmentation, 3D point cloud labeling
A. Computer vision annotation: Bounding boxes, polygon annotation, image segmentation, keypoint annotation
B. Natural language annotation: Named entity recognition (NER), sentiment analysis, audio/text translation, Reinforcement Learning from Human Feedback (RLHF)
C. 3D annotation: 3D bounding boxes, 3D polygon annotation, 3D semantic segmentation, 3D point cloud labeling
Which industries benefit from data annotation services?
Industries that benefit from data annotation services include :
A. Healthcare: Medical image labeling for diagnostic AI.
B. Agriculture: Precision agriculture that allows farmers to optimize crop yields, reduce waste and make data-driven decisions.
C. Retail: Sentiment analysis and personalized recommendations.
D. Finance: Fraud detection and risk assessment.
A. Healthcare: Medical image labeling for diagnostic AI.
B. Agriculture: Precision agriculture that allows farmers to optimize crop yields, reduce waste and make data-driven decisions.
C. Retail: Sentiment analysis and personalized recommendations.
D. Finance: Fraud detection and risk assessment.
What makes Aya Data's data annotation services stand out?
Aya Data combines cutting-edge technology, a team of experienced annotators, and a commitment to quality. Our services are scalable, cost-effective, and designed to meet the unique needs of clients across the UK, US, Europe and Africa.
How long does it take to complete a data annotation project?
The timeline for a data annotation project depends on its size, complexity, and specific requirements. Aya Data’s efficient workflows and expert teams ensure quick turnaround times without compromising quality.
How can I get started with Aya Data’s data annotation services?
Getting started is simple! Contact Aya Data to discuss your project requirements, and our team will provide you with a customized solution to meet your AI and machine learning goals.
Data Acquisition
What types of data acquisition services does Aya Data offer?
Aya Data collects data from a wide range of sources, including field data collection, web scraping, surveys, and partnerships, to meet diverse customer needs.
How does Aya Data ensure the quality and relevance of acquired data?
We prioritize accurate and relevant data acquisition by thoroughly understanding client needs and employing advanced validation techniques.
Can Aya Data acquire data for specialised or niche industries?
We can source data for specialized industries, including precision agriculture, advanced healthcare, and geospatial applications.
What industries benefit from Data Acquisition?
Industries like healthcare, agriculture, automotive and retail/ finance benefit from data acquisition for applications like diagnostics, crop monitoring, autonomous driving, and customer insights. Why Aya Data? We provide quality data acquisition to meet industry-specific requirements.
How does Aya Data handle data privacy and security during acquisition?
We prioritize data privacy and security during acquisition, adhering to regulations (GDPR, SOC II, ISO 9001, HIPAA,). Our data governance framework and team training ensure ethical data collection and compliance.
What makes Aya Data's data acquisition services unique?
We provide cost-effective, customized data solutions in challenging fields such as robotics, healthcare, and agriculture.
Can Aya Data assist with ongoing data collection for long-term projects?
Yes, we can help you set up sustainable data pipelines for long-term projects using methods like IoT sensors, drone surveys, and field data collection to create comprehensive time-series datasets for AI model training.
AI Consulting
What AI consulting services does Aya Data offer?
Aya Data acquires hard-to-find data across various industries using methods including field data collection, web scraping, surveys, and partnerships. We leverage drone imagery, sensor data, and our extensive partner network to access unique data sources for diverse industries.
How does Aya Data approach AI model development for clients?
We collaborate closely with clients to understand their challenges and goals. Our data scientists develop custom models, using both traditional machine learning and cutting-edge deep learning. We leverage and fine-tune pre-trained models for optimal performance and efficiency.
Can Aya Data help with deploying AI models in production environments?
We help clients deploy AI models into production, ensuring reliability and scalability. We use containerisation and cloud platforms, and implement continuous monitoring and RLHF to improve model performance.
What industries does Aya Data have experience in for AI consulting?
Aya Data has diverse AI experience in multiple industries, including agriculture, healthcare, finance, and robotics. We have also developed solutions for precision farming, medical image analysis, and natural language processing in African languages.
Why do businesses need AI consulting?
AI consulting helps businesses identify opportunities, avoid pitfalls and implement AI solutions effectively. It ensures ROI and aligns AI strategies with business goals. Why Aya Data? Our expertise ensures you get quality AI solutions that drive measurable results.
How does Aya Data ensure the ethical development and deployment of AI?
We prioritize ethical AI development by ensuring data privacy, addressing biases, and considering societal impact. We work with clients to develop responsible AI strategies.
What makes Aya Data's AI consulting services stand out from competitors?
We provide cost-effective, high-quality AI solutions by combining our understanding of African and global markets with AI expertise and partnerships with leading institutions.
Computer Vision Annotation
What are computer vision annotation services?
Computer vision annotation services involve labeling images or videos to train AI models. This includes tagging objects, bounding boxes, segmentation, and keypoints to help machines recognize and interpret visual data accurately.
Why is image annotation important for AI?
Image annotation provides labeled datasets essential for training AI models. It improves accuracy in tasks like object detection, facial recognition and autonomous driving by teaching machines to identify patterns and objects.
What types of image annotation are used in computer vision?
Common types include bounding boxes, polygon annotation, semantic segmentation, keypoint annotation, and landmark annotation. Each type serves specific AI applications like object detection, medical imaging, or facial recognition.
What industries use computer vision annotation?
Industries like healthcare, automotive, retail, agriculture, and security use computer vision annotation for applications such as medical imaging, self-driving cars, inventory management and surveillance systems.
What tools are used for computer vision annotation?
Popular tools include Labelbox, SuperAnnotate, CVAT and VGG Image Annotator. These tools offer features like automation, collaboration and support for various annotation types.
What are the challenges in computer vision annotation?
Challenges include handling large datasets, maintaining annotation accuracy, managing costs, and ensuring consistency across diverse data types and formats.
What is the difference between 2D and 3D annotation?
2D annotation labels objects in flat images, while 3D annotation adds depth and volume, often used for LiDAR data in autonomous vehicles or 3D modeling.
How do you ensure quality in computer vision annotation?
Quality is ensured through expert annotators, rigorous QA processes, and tools that validate accuracy, consistency and adherence to project guidelines.
3D Annotation Services
What are 3D annotation services?
3D annotation services involve labeling 3D data like point clouds, LiDAR or CAD models. It is used for applications such as autonomous driving, robotics and augmented reality.
Why is 3D annotation important for autonomous vehicles?
3D annotation helps self-driving cars understand their environment by labeling objects like pedestrians, vehicles and road signs in 3D space, ensuring accurate navigation and safety.
What tools are used for 3D annotation?
Tools like 3D BAT, Annotate.io, and Supervisely support 3D annotation for LiDAR, point clouds and 3D models, offering precision and scalability.
What is 3D LiDAR annotation?
3D LiDAR annotation involves labeling 3D point cloud data from LiDAR sensors, used in autonomous vehicles and robotics for object detection and environment mapping.
What is photogrammetry and LiDAR?
Photogrammetry uses photographs to create 3D models. LiDAR uses laser light to create 3D maps. Combining these technologies produces highly detailed and accurate 3D geospatial data.
What is LiDAR best used for?
LiDAR is best used for:
A. Mapping terrain and vegetation for environmental monitoring.
B. Autonomous vehicle navigation and obstacle avoidance.
C. Urban planning and infrastructure development.
D. Archaeology, to uncover hidden structures beneath the ground or vegetation.
E. Forestry to estimate biomass and tree heights.
A. Mapping terrain and vegetation for environmental monitoring.
B. Autonomous vehicle navigation and obstacle avoidance.
C. Urban planning and infrastructure development.
D. Archaeology, to uncover hidden structures beneath the ground or vegetation.
E. Forestry to estimate biomass and tree heights.
How do you ensure accuracy in 3D annotation?
Accuracy is ensured through skilled annotators, advanced tools and multi-stage quality checks to validate spatial and contextual precision.
Conversational AI /AyaSpeech
What is AyaSpeech, and what services does it offer?
AyaSpeech offers a comprehensive range of services designed to meet diverse language processing needs globally. These include speech-to-text (STT) which accurately transcribes spoken language into written text, and text-to-speech (TTS) that converts written text into natural-sounding speech. AyaSpeech also provides machine translation, enabling real-time translation between multiple language pairs for cross-lingual communication
Which languages does AyaSpeech support?
AyaSpeech has developed high-performance speech models for several African languages, including Twi, Ga, Ewe, Dagbani, and Hausa. We continually expand our language offerings based on market demand and client needs. Our focus on low-resource languages sets us apart in the speech technology market.
How accurate are AyaSpeech's transcription and translation services?
AyaSpeech utilises advanced AI models trained on high-quality, diverse datasets to ensure accuracy. For instance, in a project transcribing American police radio communications, we achieved a 95% accuracy rate, a significant improvement over initial automated methods. We continuously refine our models to improve performance across various accents and dialects.
Can AyaSpeech be integrated into existing communication systems?
Yes, AyaSpeech is designed for seamless integration into existing communication systems. We provide APIs that allow our speech technologies to be incorporated into various applications, from call centre software to mobile apps. Our team works closely with clients to ensure smooth integration and optimal performance within their existing infrastructure.
How does AyaSpeech handle data privacy and security?
Data privacy and security are top priorities for AyaSpeech. We adhere to strict data protection regulations, including GDPR, SOC II, ISO 27001, and local privacy laws. Our systems are designed with security in mind, implementing encryption and secure data handling practices. We also offer on-premises deployment options for clients with specific data security requirements.
EUDR Compliance
What is the purpose of Country Benchmarks?
The European Commission will create a centralized database of country risk assessments, known as "country benchmarks," to simplify due diligence and enforcement. Countries will be classified as low, standard, or high risk based on their deforestation link. Operators sourcing from low-risk countries will follow a simplified due diligence process but must still ensure their supply chains remain free from non-compliant products.
When will the Country Benchmarks be available?
The country benchmark list, outlining risk levels for enforcement, is scheduled for publication by June 30, 2025. High-risk countries will face stricter monitoring, while low-risk ones will have a more streamlined approach.
What are the application dates for EUDR compliance?
Following postponement of the EUDR implementation, the new application date for all operators and traders is December 30, 2025. For micro and small businesses established before December 31, 2020, compliance starts on June 30, 2026, except for wood products under the EU Timber Regulation (EUTR), which remain subject to the December 30, 2025 deadline.
Is packaging affected by the EUDR compliance requirement?
No, packaging materials used solely to support, protect, or carry a product are exempt from EUDR compliance, regardless of their CN code. This includes paper and cardboard packaging (e.g., CN 4819). User manuals are also exempt unless sold separately.
What does forest degradation mean?
The EUDR defines forest degradation based on FAO standards, referring to structural changes in forest cover. This includes converting primary or naturally regenerating forests into plantation forests, other wooded land, or planted forests. Additionally, compliance with production laws is assessed across eight key legal categories, covering:
A. Land use rights
B. Environmental protection
C. Forest management and biodiversity conservation
D. Third-party rights
E. Labor rights
F. Human rights under international law
G. Free, prior, and informed consent (UN Declaration on Indigenous Rights)
H. Tax, anti-corruption, trade, and customs regulations
A. Land use rights
B. Environmental protection
C. Forest management and biodiversity conservation
D. Third-party rights
E. Labor rights
F. Human rights under international law
G. Free, prior, and informed consent (UN Declaration on Indigenous Rights)
H. Tax, anti-corruption, trade, and customs regulations
What does deforestation-free mean?
Under the EUDR, deforestation-free means that products must not come from land deforested after December 31, 2020 and must comply with local production laws. Deforestation is defined as converting forests to agricultural use, whether human-induced or not. For wood-containing products, an extra requirement applies: the wood must be harvested without causing forest degradation after the same cut-off date.
Generative AI
What is Generative AI?
Generative AI is a type of artificial intelligence that creates text, images, audio, and other content based on input prompts. It learns patterns from vast datasets to generate realistic and contextually relevant outputs, enhancing automation, creativity, and decision-making across various industries.
What are the benefits of Generative AI?
Generative AI offers several key advantages, including automating the content creation process, making email responses more effortless, and realistically representing individuals. Additionally, it helps craft coherent narratives and summarize complex information effectively while streamlining content generation to align with specific styles.
What are key challenges of Generative AI?
Generative AI faces several challenges, including difficulties in identifying content sources and assessing their biases. The realistic nature of generated content can make it hard to detect inaccuracies, and adapting to new contexts can be complex. Additionally, the results may sometimes reflect bias, prejudice, or even harmful content.
Which businesses are most likely to benefit from generative AI solutions?
Businesses in content creation, marketing, customer service, e-commerce, healthcare, finance, and software development can greatly benefit from generative AI. It enhances automation, personalizes customer interactions, generates insights, and streamlines workflows, making operations more efficient and scalable across various industries.
What makes Aya Data a reliable generative AI development company?
Aya Data stands out as a reliable generative AI development company by delivering high-quality solutions with continuous support. From development to post-deployment maintenance, we ensure your AI system effectively addresses current challenges while preparing your organization for future advancements.
Natural Language Processing
What are natural language processing services?
NLP services involve analyzing and processing human language to enable AI applications like chatbots, sentiment analysis, and language translation.
Why is NLP important for businesses?
NLP helps businesses automate customer support, analyze feedback, and extract insights from text data, improving efficiency and decision-making.
What are the common NLP techniques?
Techniques include tokenization, named entity recognition (NER), sentiment analysis, machine translation, and text summarization, used for various AI applications.
How does NLP work in chatbots?
NLP enables chatbots to understand and respond to user queries by analyzing text, identifying intent, and generating contextually relevant responses.
Can NLP be used for voice assistants?
Yes, NLP powers voice assistants like Siri and Alexa by converting speech to text, understanding commands, and generating spoken responses.
What industries use NLP services?
Industries like healthcare, finance, retail and customer service use NLP for applications like medical record analysis, fraud detection and personalized marketing.
What is sentiment analysis in NLP?
Sentiment analysis uses NLP to determine the emotional tone of text, helping businesses gauge customer opinions and feedback from reviews or social media polls.
Healthcare
What are medical data annotation services?
Medical data annotation is the process of labeling medical data so AI models can be trained to make accurate medical predictions and diagnoses. Aya Data provides high-quality medical annotations for reliable healthcare insights and outcomes.
Why is medical data annotation important for healthcare AI?
Medical data annotation is essential for training AI models in healthcare. Aya Data's expert annotators ensure accurate labeling, which improves AI performance in diagnostics and medical applications.
What types of medical data does Aya Data annotate?
At Aya Data, we offer annotation services for a wide range of medical data types, including medical imaging (X-rays, MRIs, CT scans), electronic health records (EHR), pathology reports, clinical texts and notes, as well as wearable device data. Why Aya Data? At Aya Data, our deep understanding of healthcare data ensures your annotations are precise, tailored to your specific needs and fully compliant with industry standards (ISO).
How does Aya Data ensure the quality and accuracy of medical data annotations?
At Aya Data, we use a combination of skilled medical experts and advanced AI tools to ensure the highest level of accuracy. All annotations are reviewed by qualified professionals to meet strict industry standards (ISO). Why Aya Data? We adhere to global healthcare regulations and best practices, providing annotations that improve the performance of your medical AI models while ensuring data privacy and security.
How can medical data annotation services help improve my healthcare AI model?
Aya Data's accurate annotations and custom solutions accelerate the development of your healthcare AI models, improving their performance and accuracy to deliver better patient care.
What industries benefit most from medical data annotation services?
Medical data annotation services are vital for industries like healthcare, pharmaceuticals, medical research and biotech. They enhance AI-powered applications such as diagnostics, drug discovery and personalized medicine.
Are Medical Data Annotation Services HIPAA-Compliant?
Yes, Aya Data ensures that all medical data annotation processes adhere to strict compliance standards, including HIPAA, ISO 9001, GDPR and other regional data privacy regulations, to guarantee security and confidentiality.
What tools and technologies are used for medical data annotation?
Aya Data uses advanced annotation tools, AI-assisted platforms and human expertise to deliver accurate results. These technologies enable efficient labeling of medical images, texts, and audio data for AI applications.
Robotics
What is robotics training?
Robotics training uses AI and machine learning to teach robots tasks. Aya Data provides expert robotics training solutions to improve automation and efficiency.
Why is robotics training important?
Robotics training is essential for industries like manufacturing, healthcare, and logistics because it allows robots to perform complex tasks accurately and efficiently. Aya Data provides tailored robotics training to increase productivity and reduce errors.
What types of data are used in robotics training?
Robotics training uses diverse datasets like 2d/3d images and sensor data. We specialise in annotating these datasets to enable advanced robotics applications.
What industries benefit from robotics training?
Robotics training is valuable across industries like manufacturing, healthcare, logistics and autonomous vehicles. Aya Data provides tailored solutions to meet each industry's specific needs.
What are robotics annotation services?
Robotics annotation involves labeling data like images, videos, and sensor data to train AI models for robotic perception, navigation, and object manipulation.
What types of data are annotated for robotics?
Data includes 2d/3d images, lidar point clouds, and sensor data, annotated for tasks like object detection, path planning and gesture recognition.
What are the challenges in robotics annotation?
Challenges include handling diverse data types, ensuring real-time accuracy and managing the high computational requirements for robotics applications.
Agriculture
What Is AI Farming and How Does It Benefit Agriculture?
AI farming uses artificial intelligence to optimize agriculture and boost yield. Aya Data provides tailored AI solutions for enhanced productivity and sustainability.
How Can AI Be Used to Improve Crop Yield?
AI analyzes historical and real-time data to predict planting times, detect diseases, and optimize fertilizer and irrigation. This ensures healthier crops and higher yields. Why Aya Data? We use machine learning and satellite imagery to deliver actionable insights, maximizing yield while minimizing waste.
What Makes Aya Data a Leader in AI Farming Solutions?
Aya Data combines AI, machine learning, and agronomy expertise to create sustainable farming solutions. We help farmers adapt to climate change, reduce environmental impact, and increase profitability. What Makes Us Different:
A. AI tailored to local farming needs.
B. Real-time analytics with advanced algorithms.
C.Proven success in agricultural innovation.
A. AI tailored to local farming needs.
B. Real-time analytics with advanced algorithms.
C.Proven success in agricultural innovation.
What are agriculture annotation services?
Agriculture annotation involves labeling data like satellite images, drone footage, and sensor data to train AI models for crop monitoring, yield prediction, and pest detection.
Why is annotation important for AI in agriculture?
Annotation helps AI analyze crop health, optimise irrigation, and detect diseases, enabling precision farming and improving agricultural productivity.
What types of data are annotated in agriculture?
Data includes satellite imagery, drone videos, soil sensor data, and plant images, annotated for tasks like crop classification and disease detection.
How is drone imagery used in agriculture annotation?
Drone imagery is annotated to monitor crop health, identify weeds, and assess field conditions, providing actionable insights for farmers.
What are the challenges in agriculture annotation?
Challenges include handling large datasets, ensuring accuracy in diverse environmental conditions, and managing costs for large-scale farming operations.
AyaGrow
What is AyaGrow and how does it benefit farmers?
AyaGrow is our AI-powered crop and farm intelligence solution that combines aerial imaging, on-ground data, and advanced analytics to revolutionise plantation management. It provides farmers with actionable insights for precision farming, including tree inventory, yield forecasting, and health analysis. Through data-driven decision-making, AyaGrow helps optimise resource allocation, reduce input costs, and increase crop yields.
What crops does AyaGrow support?
AyaGrow primarily focuses on four main crops: oil palm, mango, banana, and rubber. We selected these based on market size, potential for AI to solve key issues, and existing expertise. However, our platform is designed to be scalable, and we're capable of supporting a wider range of crops based on market demand and client needs.
How does AyaGrow collect and process data?
AyaGrow uses multiple data sources, including drone imagery, satellite data, and field surveys. Our AI models process this data to provide insights such as tree count, health analysis, and yield estimation. The platform integrates with various data collection methods, including client-owned drones, Aya Data's drone partners, and mobile apps for field data collection.
Can AyaGrow integrate with existing farm management systems?
Yes, AyaGrow is designed to be flexible and can integrate with existing farm management systems through APIs. For larger farms or organisations with established systems, we can provide AI model outputs that can be incorporated into their current workflows. This allows clients to enhance their existing processes with advanced AI-driven insights.
How does AyaGrow help with precision agriculture and resource optimisation?
AyaGrow enables precision agriculture by providing tree-level analytics and actionable insights. It helps identify specific areas requiring intervention, such as nutrient deficiencies or pest infestations. This allows for targeted application of inputs like fertilisers and pesticides, reducing waste and optimising resource usage while improving overall crop health and yield.
How is AyaGrow relevant to DFIs?
AyaGrow is an AI-powered crop and field management platform that delivers precision insights to enhance agricultural productivity. By combining aerial imagery from satellites and drones, field data, and advanced AI analytics, AyaGrow enables DFIs to optimize operations, make data-driven decisions, and drive measurable economic impact in both commercial and smallholder farming investments.
How does AyaGrow support DFIs in their investment processes?
DFIs conduct climate risk assessments, due diligence, and business reviews to evaluate investment opportunities. AyaGrow streamlines these processes with tools such as yield mapping, crop health assessments, tree counting, and yield forecasting, delivering accurate data at scale to inform investment decisions. Additionally, mobile data collection tools provide real-time insights into farmers and their farms, enhancing portfolio reporting and decision-making.
How can AyaGrow improve operational efficiency for DFIs?
DFIs often rely on manual inspections and specialist teams to assess farms, which can be both time-consuming and costly. AyaGrow automates processes like field assessments, health monitoring, and smallholder profiling, enabling faster, data-driven insights. This significantly reduces operational expenses while improving the speed and accuracy of assessments.
How does AyaGrow help DFIs address climate and sustainability goals?
AyaGrow provides tools for flood and drought management, crop identification, and health monitoring, allowing DFIs to assess and mitigate climate-related risks effectively. By delivering sustainable solutions to monitor and optimize farm performance, AyaGrow ensures that agricultural investments are resilient, environmentally sustainable, and impactful.
What makes AyaGrow a valuable tool for DFIs investing in agriculture?
AyaGrow combines advanced AI, automation, and robust ground-truthing capabilities to provide highly accurate insights such as tree counting, crop health and disease assessment, and yield forecasting. This empowers DFIs to make well-informed investment decisions, reduce costs, and maximize their impact across agricultural value chains.
Sales Support
What kind of sales support does Aya Data offer to potential clients?
Aya Data provides comprehensive sales support, including detailed product demonstrations, customised proof of concept (PoC) development, and flexible engagement models at competitive prices. Our team of sales development representatives and domain experts work closely with potential clients to understand their specific needs and demonstrate how our AI solutions can address their challenges.
Can Aya Data provide case studies or references from similar projects?
Yes, we have a portfolio of case studies showcasing successful implementations across various industries. For instance, we've worked with agricultural companies to develop AI-powered crop management systems, and with healthcare providers to digitise and analyse medical records. We can provide relevant case studies and, where possible, connect potential clients with existing customers for references.
How does Aya Data handle pricing for its services?
Our pricing model is transparent and tailored to each client's needs. For services like AyaGrow, we typically charge per hectare, with different rates for drone and satellite insights. Pricing for data annotation and acquisition services depends on the project's scope and complexity. We offer flexible pricing options, including subscription models for ongoing services and project-based pricing for one-off engagements.
How does Aya Data support clients after the initial sale?
We provide ongoing support and consultation to ensure client success. This includes technical support, regular performance reviews, and continuous optimisation for deployed solutions. For services like AyaGrow and AyaSpeech, we offer training and onboarding support to help clients maximise the value of our platforms. Our customer success team maintains regular communication to address any issues and gather feedback for future improvements.
Didn’t Find The Answer You’re Looking For?
Call us, email us or reach out on social media.
