#AzureAIsearch

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Data Zones Improve Enterprise Trust In Azure OpenAI Service

The trust of businesses in the Azure OpenAI Service was increased by the implementation of Data Zones.

Data security and privacy are critical for businesses in today’s quickly changing digital environment. Microsoft Azure OpenAI Service provides strong enterprise controls that adhere to the strictest security and regulatory requirements, as more and more businesses use AI to spur innovation. Anchored on the core of Azure, Azure OpenAI may be integrated with the technologies in your company to assist make sure you have the proper controls in place. Because of this, clients using Azure OpenAI for their generative AI applications include KPMG, Heineken, Unity, PWC, and more.

With over 60,000 customers using Azure OpenAI to build and scale their businesses, it is thrilled to provide additional features that will further improve data privacy and security capabilities.

Introducing Azure Data Zones for OpenAI

Data residency with control over data processing and storage across its current 28 distinct locations was made possible by Azure OpenAI from Day 0. The United States and the European Union now have Azure OpenAI Data Zones available. Historically, variations in model-region availability have complicated management and slowed growth by requiring users to manage numerous resources and route traffic between them. Customers will have better access to models and higher throughput thanks to this feature, which streamlines the management of generative AI applications by providing the flexibility of regional data processing while preserving data residency within certain geographic bounds.

Azure is used by businesses for data residency and privacy

Azure OpenAI’s data processing and storage options are already strong, and this is strengthened with the addition of the Data Zones capability. Customers using Azure OpenAI can choose between regional, data zone, and global deployment options. Customers are able to increase throughput, access models, and streamline management as a result. Data is kept at rest in the Azure region that you have selected for your resource with all deployment choices.

Global deployments: With access to all new models (including the O1 series) at the lowest cost and highest throughputs, this option is available in more than 25 regions. The global backbone of the Azure resource guarantees optimal response times, and data is stored at rest within the customer-selected

Data Zones: Introducing Data Zones, which offer cross-region load balancing flexibility within the customer-selected geographic boundaries, to clients who require enhanced data processing assurances while gaining access to the newest models. All Azure OpenAI regions in the US are included in the US Data Zone. All Azure OpenAI regions that are situated inside EU member states are included in the European Union Data Zone. The upcoming month will see the availability of the new Azure Data Zones deployment type.

Regional deployments: These guarantee processing and storage take place inside the resource’s geographic boundaries, providing the highest degree of data control. When considering Global and Data Zone deployments, this option provides the least amount of model availability.

Extending generative AI apps securely using your data

Azure OpenAI allows you to extend your solution with your current data storage and search capabilities by integrating with hundreds of Azure and Microsoft services with ease. Azure AI Search and Microsoft Fabric are the two most popular extensions.

For both classic and generative AI applications, Azure AI search offers safe information retrieval at scale across customer-owned content. This keeps Azure’s scale, security, and management while enabling document search and data exploration to feed query results into prompts and ground generative AI applications on your data.

Access to an organization’s whole multi-cloud data estate is made possible by Microsoft Fabric’s unified data lake, OneLake, which is arranged in an easy-to-use manner. Maintaining corporate data governance and compliance controls while streamlining the integration of data to power your generative AI application is made easier by consolidating all company data into a single data lake.

Azure is used by businesses to ensure compliance, safety, and security

Content Security by Default

Prompts and completions are screened by a group of classification models to identify and block hazardous content, and Azure OpenAI is automatically linked with Azure AI Content Safety at no extra cost. The greatest selection of content safety options is offered by Azure, which also has the new prompt shield and groundedness detection features. Clients with more stringent needs can change these parameters, such as harm severity or enabling asynchronous modes to reduce delay.

Entra ID provides secure access using Managed Identity

In order to provide zero-trust access restrictions, stop identity theft, and manage resource access, Microsoft advises protecting your Azure OpenAI resources using the Microsoft Entra ID. Through the application of least-privilege concepts, businesses can guarantee strict security guidelines. Furthermore strengthening security throughout the system, Entra ID does away with the requirement for hard-coded credentials.

Furthermore, Managed Identity accurately controls resource rights through a smooth integration with Azure role-based access control (RBAC).

Customer-managed key encryption for improved data security

By default, the information that Azure OpenAI stores in your subscription is encrypted with a key that is managed by Microsoft. Customers can use their own Customer-Managed Keys to encrypt data saved on Microsoft-managed resources, such as Azure Cosmos DB, Azure AI Search, or your Azure Storage account, using Azure OpenAI, further strengthening the security of your application.

Private networking offers more security

Use Azure virtual networks and Azure Private Link to secure your AI apps by separating them from the public internet. With this configuration, secure connections to on-premises resources via ExpressRoute, VPN tunnels, and peer virtual networks are made possible while ensuring that traffic between services stays inside Microsoft’s backbone network.

The AI Studio’s private networking capability was also released last week, allowing users to utilize its Studio UI’s powerful “add your data” functionality without having to send data over a public network.

Dedication to Adherence

It is dedicated to helping its clients in all regulated areas, such as government, finance, and healthcare, meet their compliance needs. Azure OpenAI satisfies numerous industry certifications and standards, including as FedRAMP, SOC 2, and HIPAA, guaranteeing that businesses in a variety of sectors can rely on their AI solutions to stay compliant and safe.

Businesses rely on Azure’s dependability at the production level

GitHub Copilot, Microsoft 365 Copilot, Microsoft Security Copilot, and many other of the biggest generative AI applications in the world today rely on the Azure OpenAI service. Customers and its own product teams select Azure OpenAI because it provide an industry-best 99.9% reliability SLA on both Provisioned Managed and Paygo Standard services. It is improving that further by introducing a new latency SLA.

Announcing Provisioned-Managed Latency SLAs as New Features

Ensuring that customers may scale up with their product expansion without sacrificing latency is crucial to maintaining the caliber of the customer experience. It already provide the largest scale with the lowest latency with its Provisioned-Managed (PTUM) deployment option. With PTUM, it is happy to introduce explicit latency service level agreements (SLAs) that guarantee performance at scale. In the upcoming month, these SLAs will go into effect. Save this product newsfeed to receive future updates and improvements.

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11x Faster Search for Generative AI with Azure AI Search

Azure AI Search

In order to assist customers developing generative AI applications that are ready for production, Azure is pleased to announce today some major updates to Azure AI Search. In order to enable customers to run retrieval augmented generation (RAG) at any scale without sacrificing cost or performance, Azure AI Search has significantly increased storage capacity and vector index size at no additional cost.

This article will explain how clients can

Can use today’s changes to achieve more scalability at a lower cost.

Put their large RAG workloads in the hands of Azure AI Search.

To innovate in previously unthinkable ways, use sophisticated search techniques to navigate complex data.

Introducing Azure AI Search, which offers greater performance and scalability at a cheaper price

With much increased vector and storage capacity, Azure AI Search can now provide users with higher scalability, better performance, and more data for their money.

In some regions, the Basic and Standard tiers of Azure AI Search now have more available capacity and compute.

Users are going to see up to a

11 times larger vector index.

A sixfold rise in overall storage.

Indexing and query throughput improvements of two times.

With these adjustments, clients can provide excellent user and interaction experiences at any size. With just one search instance, users can scale their generative AI applications to a multi-billion vector index without sacrificing efficiency or speed.

Providing a reliable enterprise retrieval system to support sizable RAG-based applications

For the management of their mission-critical enterprise search and generative AI applications, more than half of Fortune 500 companies rely on Azure AI Search. Azure AI Search is used by OpenAI, Otto Group, KPMG, and PETRONAS to support workloads related to retrieval augmented generation (RAG).

OpenAI had to make sure their retrieval system could handle previously unheard-of demand and scale when they unveiled their Assistant API and RAG-powered “GPTs” at OpenAI DevDay 2023. Because of Azure AI Search’s ability to handle their massive, internet-scale RAG workloads, OpenAI turned to it.

Azure AI Search now offers search functionality to products such as the GPT Store and supports RAG capabilities for ChatGPT, GPTs, and the Assistant API. Azure AI Search is the retrieval system that makes these products function whenever someone searches within them or adds a file to them.

As of November 2023, 100 million people visit ChatGPT alone each week, and over 2 million developers use its API to build applications. Three million custom GPTs were generated in the first two months after their announcement. With users from all over the world, these are enormous numbers. Really RAG on a large scale.

Using a cutting-edge, modern retrieval system to create better applications

Using just one search technique, such as vector search, is ineffective for creating generative AI applications that function as intended, as teams in the professional services, healthcare, and telecommunications industries have discovered.

Certain use cases are better served by different retrieval strategies. To cover the range of scenarios that any given application is likely to encounter, high-quality retrieval systems combine multiple techniques.

Developers can accomplish goals more quickly and efficiently by using Azure AI Search to enable applications to apply a range of strategies straight out of the box, such as hybrid retrieval and semantic reranking.

Advanced RAG is used by Telus Health to provide a customer support application

Telus Health is a Canadian-based company that leads the way in offering technology-based services and solutions to insurers, individuals, employers, and healthcare professionals. In order to address user questions regarding particular health plans and provide assistance with using their website, the company launched a customer support platform. All of the requirements could not be met by the first implementation, which was based only on vector search. Telus Health resorted to Azure AI Search as a result, which is renowned for its cutting-edge, extensive suite of search technologies.

The Guide Team at Telus Health played a key role in developing their search approach and making efficient use of AI Search to improve the platform. Telus Health made it possible for the system to effectively handle queries pertaining to client-specific documents as well as those utilising the company website by broadening their retrieval strategy and introducing hybrid search with semantic reranking. This strategic improvement, made possible by Azure AI Search, has greatly increased the platform’s accuracy and responsiveness and demonstrates Telus Health’s dedication to providing top-notch customer service.

NIQ Brandbank uses multi-vector retrieval to enable brands to maximise their online presence

Fast-moving consumer goods (FMCG) brands can outperform their rivals by using NIQ Brandbank’s solutions to provide rich, pertinent content and imagery for their digital shelf.

With data-driven, practical advice and insights that demonstrate how their product content compares to competitors in the market, NIQ Brandbank’s Content Health+ solution enables brands to maximise their online presence.

The application helps brands increase sales, improve product placement across retailer search results, and improve their online presence with its straightforward, user-friendly format.

In order to determine which product attributes affect organic placement on the digital shelf, Content Health+ draws from research conducted by an NIQ Data Impact team. The application uses multi-vector search on the backend to search the research that is stored in both text and images. Search reranking is used to present the most relevant results. This feature makes excellent recommendations about the kind of content that a brand should prioritise in order to boost sales and performance.

Content Health+ was developed using hybrid multi-vector search and semantic ranking to ensure that the application functions as intended. Combining different retrieval techniques allows more ideas and opportunities to be realised for e-commerce and recommendation apps.

Find out more about Azure AI Search

They are facilitating the AI systems’ ability to retrieve information at scale by making these announcements today. With Azure AI Search’s cutting-edge retrieval technology and an enterprise-ready foundation, customers can innovate with confidence.

Leading search and information retrieval platform for RAG Azure AI Search, an AI-powered platform for information retrieval, assists developers in creating generative AI apps and rich search experiences by fusing enterprise data with large language models. Provide search capabilities for all mobile applications, internal search applications, and software as a service (SaaS) apps.

Simplify the creation and provision of search solutions

Simplify the process of creating search indexes and ingesting data by integrating them with Azure storage solutions, RESTful APIs, and SDKs. Implement a search service that is fully configured and offers user-friendly features like synonyms, faceting, scoring, and geo-search. Steer clear of the operational costs associated with debugging index corruption, keeping an eye on service availability, or manually scaling during traffic spikes.

Showcase the most pertinent outcomes for your users

Utilise cutting-edge deep learning models from Bing and Microsoft Research to give your apps results that are pertinent and contextual. Use the semantic search feature to provide customers with substantially better results, gain a deeper understanding of their search terms, and increase customer engagement. Knowledge mining and summary results are also made possible by semantic search, providing your users with quick snippets without making them scroll through a tonne of results.

Use Azure OpenAI Service to develop apps for the next generation

To apply the most sophisticated AI language models to your search solutions that use your own data as the foundation for responses, combine Azure AI Search with Azure OpenAI Service. ChatGPT, an Azure OpenAI service, allows you to retrieve enterprise data from knowledge bases using conversational language.

Adapt search features with AI integrations

Customise the search process to fit your organization’s particular needs. Key phrase extraction, language detection, optical character recognition (OCR), image analysis, translation, and role-based access control (RBAC) are just a few of the customizable features that Azure AI Search provides. Utilize the integration features offered by Azure AI services, such as Speech, Vision, Language, and Azure OpenAI Service, to enhance the conversion of unstructured, raw data into searchable content.

Scale to handle heavy traffic loads and big datasets

Easily index and search through enormous volumes of data, regardless of the size of your company, to provide excellent search results for your users without worrying about infrastructure management. Your search solution will be scalable as your company expands thanks to Azure AI Search’s ability to manage massive data loads and high traffic loads.

Use AI sensibly

With Azure AI Search, you can get access to cloud search tools, guidelines, and other resources to assist you in developing a responsible AI solution. Go through Microsoft’s responsible AI guidelines.

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