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.

​

​

​

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 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).

​

​

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)

​

​

​