Automatic email reply with appropriate product specification document
Automated Email Query Resolution System
The Akaike Edge
As per the data across the industries
Automated email responses enhances the business productivity by 0%
Email classification saves manual efforts by 0%
Automated information extraction reduces cost by 0%
Understand the email intent and extract relevant information
One of the primary challenges was to understand the email intent if the email query was to get the appropriate product specification document. This was automated by training a binary classification model by using two different types of email texts; email text for the product specification document requirements and email text for any other purpose. After having figured out by using the classification model that if the email query is intended to get the product specification document, the relevant information is extracted from a customer email query such as product name, invoice id, and other vital specifications. For any other type of email, the query was resolved using manual intervention.
Trained the Name-Entity-Recognition model
NER (Name Entity recognition) model was trained to automatically annotate entities in the email such as product id, catalog id, reference-id, and more to clearly identify all the required attributes to fetch the relevant specification document, and the entities were saved in the database.
Extracted the product specification document from the database and the email query was settled automatically
Product id, reference Id, and similar details were used to extract the product specification document from the backend. The required document was then attached to the email query response and was settled by an automatic email reply.
Research shows that 87% of Vision AI
projects do not yield expected results
either owing to training data insufficiencies stalling the project, or being too slow to deploy. Our AI experts can help you accelerate in data sparse environments.