Which solution will meet these requirements with the LEAST development effort?
Index company documents by using Amazon Kendra. Integrate the chatbot with Amazon Kendra by using the Amazon Kendra Query API operation to answer customer questions.
Train a Bidirectional Attention Flow (BiDAF) network based on past customer questions and company documents. Deploy the model as a real-time Amazon SageMaker endpoint. Integrate the model with the chatbot by using the SageMaker Runtime InvokeEndpoint API operation to answer customer questions.
Train an Amazon SageMaker Blazing Text model based on past customer questions and company documents. Deploy the model as a real-time SageMaker endpoint. Integrate the model with the chatbot by using the SageMaker Runtime InvokeEndpoint API operation to answer customer questions.
Index company documents by using Amazon OpenSearch Service. Integrate the chatbot with OpenSearch Service by using the OpenSearch Service k-nearest neighbors (k-NN) Query API operation to answer customer questions.
Explanations:
Amazon Kendra is a fully managed search service that allows you to index company documents and makes it easy to integrate with a chatbot. By using the Kendra Query API, the chatbot can retrieve relevant answers based on the indexed documentation with minimal development effort.
Training a BiDAF network requires significant development effort for model training and fine-tuning. Additionally, deploying it as a SageMaker endpoint would involve creating and managing the endpoint, which is more complex compared to using a managed service like Kendra.
Training a SageMaker Blazing Text model would require extensive development for model training and optimization based on the documents. Additionally, this solution would be less efficient compared to using a managed service like Kendra, as it would require ongoing maintenance.
Amazon OpenSearch Service can be used for indexing, but it would require building custom retrieval and search mechanisms, and using k-NN queries is more complex compared to Kendra’s managed search capabilities. It involves more effort than the Kendra solution.