Our use of AI may not be that laudable; However, we are doing our part to bring relevant application of AI at Enterprises to enhance customer interactions and improve employee productivity.
Personalization, hyper relevant and timely information are key to higher customer satisfaction. Additionally, with ever increasing demand from customers, employees need expedient access to data and information; no matter how complex the Enterprise systems landscape may be.
Build, connect, deploy, and manage intelligent bots to interact naturally with your users on websites, apps, Cortana, Microsoft Teams, Skype, Slack, Facebook Messenger and more. Get started quickly with a complete bot-building environment.
Customizable image recognition
Automatic speech recognition and speech transcription (speech-to-text)
Customizable speech recognition and speech transcription (speech-to-text)
Customizable speech models for unique vocabularies or accents
Automatic text-to-speech
Customizable voice fonts for text-to-speech
Named Entity Recognition
Key phrase extraction
Text sentiment analysis
Web-scale, multi-lingual spell checking
Contextual spell checking
Named Entity Recognition
Key phrase extraction
Text sentiment analysis
Explicit or offensive content moderation for images and videos
Custom image and text lists to block or allow matching content
Tools for including feedback from human moderators
Automatic language detection
Automated text translation
Customizable translation
QnA extraction from unstructured text
Knowledge base creation from collections of Q&As
Semantic matching for knowledge bases
Contextual language understanding
Identify suitable algorithms and hyperparameters faster.
Train models with ease and reduce costs by autoscaling powerful GPU clusters.
Increase productivity with experiment tracking, model management and monitoring, integrated CI/CD and machine learning pipelines.
Deploy models on-premises, to the cloud and at the edge with a few lines of code.
Azure Machine Learning service integrates with any Python environment, including Visual Studio Code, Jupyter notebooks and PyCharm.
Use your favourite machine learning frameworks and tools, such as PyTorch, TensorFlow and scikit-learn.