Containers allow enterprises to build applications on their own infrastructure. It enables enforcement of strong security and data governance requirements critical for regulatory-heavy industries such as financial services, healthcare and government agencies. Azure AI services let you use the same APIs that are available in Azure, on-premises. This offers developers the flexibility to bring Azure AI services to where their data and apps reside. Customers building AI-driven applications using Azure have the option of running Docker containers on your premises, or a Docker hosting service in Azure such as Azure Kubernetes Service, Azure Container Instances, or a Kubernetes cluster deployed to Azure Stack.
At Azure AI Language and Translator, we have been helping customers across the spectrum build language and translator capabilities in their applications using containers. Here are a few more that we are announcing today.
Azure AI Translator
Announcing document translation in containers
Containers in Azure AI Translator service have been generally available for text translation since January 2022. Over the last year we have witnessed significant market demand for translator containers in the government, military, banking, and security enforcement sectors. In addition to translating text, customers want the ability to translate documents in containers as well.
Today, we are announcing containerized document translation capability in Azure AI Translator. This capability is generally available to enterprise users looking to translate complex documents across all supported languages and dialects, while preserving the original document structure and data format within customer premises.
This document translation API allows users to take the document as part of the request, have it translated, and return the translated document in the response itself.
Customers can purchase a single translator container to translate text as well as documents
For more information, refer to the following resources:
Azure AI Language
We announced the availability of Azure AI Language summarization container in October! It comes with both options – disconnected and connected containers, along with Commitment Tier pricing. Summarization in Azure AI Language provides ready-for-use solutions with task-oriented and -optimized LLM-powered models to summarize documents and conversation transcripts.
We are also announcing the availability of the pre-built Named Entity Recognition (NER) capability in containers starting today. This capability is also available in disconnected and connected containers, along with Commitment Tier pricing. With the ready-for-use solutions using task-optimized NER models, customers can identify and extract key entities from their document text. This new container option allows customers to call NER models in regions and countries beyond what is covered by the current cloud offerings.
Disconnected containers allow customers with high demands for data security and confidentiality to implement scenarios requiring natural language and translation capabilities in a fully disconnected secure environment. It is ideal for regulatory-heavy industries where data isolation is critical, such as defense, legal, healthcare, financial industries, intelligence agencies. Customers have full control over their environment, minimizing data exposure. Customers interested in disconnected containers should go through the gating process to get approved.Container options allow customers to utilize the models in more regions and countries, beyond what is supported by the cloud offering today.
With Commitment Tier pricing, customers will benefit from cost savings based on their commitment level, makingit an ideal option for customers looking to use this capability over the long term. It offers predictability in pricing, makes budget planning more straightforward, and flexibility to accommodate your specific needs and usage patterns.
For more information, refer to the following resources: