June 17, 2021
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A client in the retail business needed a way to reduce churn, better optimize its assortments, and correct inventory distortion. Using NLP and machine learning, Synerzip’s experts built a platform that interacts with humans in natural language and delivers prescriptive analytics to minimize a problem's impact.
Synerzip’s team helped a client in fuel supply chain management by actively analyzing consumption per site. They then coupled this data with external data sources to better predict what upcoming customers’ may have. These predictions allow them to manage their inventory better and reduce the cost of ownership.
Our ML teams built models to actively learn about the applicants by ‘reading’ their resumes to build a feature model. This model is then used to train a random forest model whose results classify applicants by topics. When the results were not accurate human intervention fine-tuned the learning process making better models for future use.
Achieve real benefits of AI and machine learning algorithms, computer vision, and natural language processing by streamlining disparate data sources. Build production-ready machine learning models with feedback loops to fine-tune and monitor models in production.
Answer pressing business questions with innovative and descriptive insights
Develop, deploy and productionize end-to-end machine learning solutions using proven technologies
Build human-friendly chatbots and interactive dialog systems using abundantly available text content
Build better ML models using images for text and feature extraction
Build ML models on sparsely labeled datasets using transfer learning on generic models built with abundantly available non-labeled generic data sets
Productionize your machine learning workflows with automation to version data, code and models and reduce friction between data science and operations teams
Various tools and platforms that we have real-world experience and expertise with.