We use Machine Learning, Deep Learning & NLP to extract and implement insights from the vast pools of data generated by every interaction between multiple audiences and stakeholders. We implement the feedback loops for these in web and mobile applications.
We work with multiple backend technologies to perform data collection (data connectors & adapters, Data Scraping, Noise Reduction); data Normalization (Schema Creation, Data Transformation, MetaData Management); and Data Performance Management
We first perform hypothesis development to formulate the problem and identify learning objectives. We then prepare the data pipeline or a data lake as required by the application.
We use multiple AI techniques for Supervised Learning (Linear Regression, Neural Networks etc.); and Unsupervised Learning (Principal Components Analysis, Anomaly Detection etc.) to generate actionable insights from the data. We automate the process to refine the algorithm iteratively as and when data sources and quality changes.
The actionable insights generated by AI techniques are then integrated with the business process and Decision Support Systems to create a continuous loop of improvement.
We have implemented Recommender Systems to improve discovery of relevant content for each user, AI enabled Voice & Chat interfaces to improve customer satisfaction; and Insights extraction & Sentiment Analysis.
We have worked with Alexa, Google Assistant and other Chatbot APIs and platforms.