An integrated AI/ML-drone platform that makes Agriculture more efficient, and environmental monitoring smarter.

Online Artificial Intelligence and Machine Learning services

We have assembled a diverse, multi-disciplinary team comprising experts in AI, software development, manufacturing, agriculture, education, health, and energy to provide comprehensive technical support.

Leveraging Amazon cloud services, we offer cost-effective solutions with robust functionalities, guaranteeing optimal performance.

Choose from multiple customization levels, each with its associated costs, allowing you to tailor the platform to suit your precise needs and budget.

Our platform is designed for efficiency, facilitating swift modifications and updates with minimal effort, ensuring adaptability for future needs.

We offer a variety of pricing strategies and license types, ensuring flexibility for different customers with diverse requirements and budgets.

Our platform boasts a user-friendly interface complemented by easily accessible customization tools, ensuring seamless user experience.

Enjoy multiple adaptive privacy levels tailored to your specific requirements, ensuring confidentiality and security at every level.

Experience our platform firsthand through our online interactive demo or seamlessly integrate our services via API calls.

As AI experts, we always encounter other researchers with very valuable experimental data rigorously collected in laboratories, but time and resource constraints limit the viability of applying machine learning or computer vision methods on these data, to extract information associated with this raw data. At the very beginning, we tried to help researchers in the fields such as agriculture, metallurgy, food science, biology, psychology, ophthalmology, etc. by collaborating in their research and assigning a M.E. or Ph.D. AI student to assist them. With the increased number of researchers with a similar challenge, this approach would demand rapid scaling, and our limited resources for training machine learning models on their big data was a new challenge.

We observed a very similar challenge in software companies. To boost their product in the market, many managers believe they have to add AI functionalities to their products. But hiring a team of AI experts requires large financial investment that small or medium size companies usually cannot meet. Seeing the same challenges across industries, we developed the concept of providing AI services on cloud infrastructures that are general purpose and would form the building blocks of any AI functionalities that people might usually require in their research or products. saiwa now enables customers, with only drag and drop and a few clicks, the ability to apply state-of-the-art algorithms on their own data – all without the need to understand the source codes and the way to install and employ different algorithms.

This product is aimed at a wide range of customers, including: amateur users of machine learning algorithms, owners of the businesses with pressing needs for image recognition and modification, and analysis of data; academic groups that the nature of their research includes analysis of images (such as metallurgists, bio, mining, CAT scan …) and many others. saiwa potential users include but not limited to: 1) researchers who need to collect and analyze image, video and voice data in their specific experiments, 2) software companies that are interested in adding AI functionalities to their products, 3) AI experts with interests -in comparing their own algorithms with state-of-the-art methods, and 4) other AI-interested individuals that lack necessary resources for applying machine learning and other AI algorithms. We had sufficient discussions with potential customers from all the above-mentioned categories both before and during developing the first phase. We analyzed their viewpoints, requirements and challenges to decide about saiwa features and services. Discussing with early-adopter customers will take place after saiwa passes initial test steps with its validating partners.