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Machine Learning Applications
Simplain's research and development team has been investing in emerging technologies to identify practical applications of Machine Learning / Artificial intelligence techniques that provide measure ROI to our customers. Here are some of our services in this domain.
Anamoly Detection
Anomaly detection models have practical applications in the retail supply chain. Some examples includes neural networks to predict out of stock situations and logistic regression techniques to detect anomalies in the master data set up.
Natural Language Search
Modern applications such as Simplain Vendor Portal are expected to interact with the end user using natural language. Natural language search is likely the most important practical application of NLP techniques in business applications. The idea is to improve search to include the context of the session and not just rely on key words. Simplain is working harnessing the power of large language models to create fine-tuned models that may perform better in a specific application/business settings.
Regression Models
Regression models are already used in forecasting applications for a while now. Simplain can work with the customer's specific requirements to create forecasting models that factor in not only the standard parameters available in the database, but also factor in additional, external information (such as weather forecast).
Classification and Sentiment Analysis
Sentiment analysis models can be useful in summarizing customer sentiment expressed via reviews or emails. An organization can quantify the number of negative or positive interactions with their customer base, by running sentiment analysis on exchanges(email or product reviews)
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