Projects we have worked on include dynamic pricing for a retail company, fraud detection for a financial firm, customer segmentation for a media company, image analysis for cancer detection for a healthcare company, machine learning projects related to regulation and compliance, accounting, HR, operations, technology and other functions among many other machine learning and deep learning projects.
Based on the client relationship with a cloud vendor, we work with different cloud platforms to find the right solution.
We use all open source machine learning and big data frameworks (Tensor flow, Scikit-learn, Keras, Caffe, MLlib, Hadoop, Spark and other machine learning and big data frameworks) and platforms to ensure that any new breakthrough in AI technologies can be seamlessly adapted in the future. We do not recommend locking into any AI proprietary platforms.
We have developed many chatbots for our retail, pharma, healthcare and finance clients for their customer interactions.
Time series analysis is a major form of predictions in Finance. We helped few finance clients to better manage clients money using various AI solutions.
We helped few pharma clients to predict the sales of their new drugs using AI and machine learning and historic sales data.
We helped a retail and healthcare client to segment their clients based on past purchases using AI and machine learning for better understanding of their clients and cross sell and up sell opportunities.
We helped a media company to convert large amounts of unstructured data into structured data for sentiment analysis and reputation management.
We worked with a large financial company to detect anomaly in their KYC screening process for quicker customer on boarding.
Using AI and machine learning, we helped an energy client with assets planning using historic data to help them better manage their assets and resources.
Our first goal is to understand your business and data well. Often times many vendors miss this part and go directly and try to build ML models. This is often a path to failure. We have experts in each domain and industry who understand your business well so we can develop a great ML solution.
Once we understand your use case and data well, we can build a POC.
Once POC is complete and all your stakeholders are onboard, we can do full implementation of the model(s) and productionize them. We can also help maintain the models with any requirement changes.