With YZR's API and collaborative AI platform: - Business experts spend much less time correcting, tagging and grouping textual data manually with a NLP-powered solution - Data and IT teams integrate faster and with more confidence automated textual data quality pipelines into ETLs, data lakes,...
Geographical Entity Sentiment Analysis identifies positive, negative or neutral sentiments related to geographical entities such as cities, states, countries etc. Polarity scores are calculated by identifying named entities in text and modeling sentiments to respective entities. This solution can...
Model Package - Fulfilled on Amazon SageMaker
The Hexaware Content Hub, powered by Amazon Bedrock, is revolutionizing content marketing by seamlessly integrating context, creativity, and hyper-personalization. It tailors engaging content to specific user segments, thereby enhancing campaign success and boosting engagement. This versatile...
This solution uses an unsupervised learning method that solves problem of Bias in unstructured data (Text Corpus). It identifies and reduces the bias present in the word embeddings. The user can target a specific bias (Gender, Age, Race etc.) to be identified and mitigated, without loss in semantic...
Algorithm - Fulfilled on Amazon SageMaker
This is a Extractive Question Answering model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/). It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text...
Model Package - Fulfilled on Amazon SageMaker
This is a demo product from Amazon that showcases the Marketplace experience. It was created using this sample notebook https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb. Decision Trees (DTs) are a...
Algorithm - Fulfilled on Amazon SageMaker
This is a Extractive Question Answering model built upon a Text Embedding model from [PyTorch Hub](https://pytorch.org/hub/huggingface_pytorch-transformers/). It takes as input a pair of question-context strings, and returns a sub-string from the context as a answer to the question. The Text...
Model Package - Fulfilled on Amazon SageMaker
With every industry moving towards the fast-paced adoption of Generative AI, taking the right steps in your digital transformation journey is even more critical. Whether it is accelerating innovation, improving productivity, bringing in process efficiencies, or increasing revenue, we can help you...
Legal entity ownership extraction is an NLP solution that helps identify and classify legal parent and subsidiary organization names in an unstructured text. The solution takes a text file as input. The text can be sourced from documents such as financial statements and legal documents. The...
Model Package - Fulfilled on Amazon SageMaker
This is a Sentence Pair Classification model built upon a Text Embedding model from [Hugging Face](https://huggingface.co/bert-large-cased). It takes a pair of sentences as input and classifies the input pair to 'entailment' or 'no-entailment'. The class label entailment implies the second sentence...
Model Package - Fulfilled on Amazon SageMaker
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