Azure AI Search: What is it, and how does it help my AI projects?

Here’s a secret for you. While some of you may know me already from my Pluralsight training courses on everything Azure, what you definitely do not know is that much of my material is ethically tested on my cat, Mr. Pepé Le Mew. Cats have a notoriously short attention span, and if I can get Pepé to care about Azure even a little, then I’ve hit my mark.

(Don’t judge! If you think talking to cats is odd, you’ve clearly never owned one)

Anyway, I was recently talking about Azure AI Search with him, and how it’s amazing at secure information retrieval at scale. However, Pepé kept licking his paw — it seemed I was boring him. However, when I mentioned how new and existing AI projects could benefit from Azure AI search, Pepé’s whiskers twitched ever so slightly. He still didn’t look at me, but I knew I’d caught his interest. 

Right then, I knew I’d hit a winner. And so here I am, sharing my learnings with you on how to boost your AI projects with Azure AI Search, and secretly wondering what secret project Pepé’s working on to have it catch his interest (Mouse identification with Azure AI Vision, perhaps? Clearly it’s not AI, but cats we need to worry about taking over the world.) 

What is Azure AI Search?

Azure AI Search, previously Azure Cognitive Search, is a cloud-based service for searching within your privately curated data. It uses a combination of Microsoft’s AI and JSON-based indexes to provide fast, relevant search results. It’s similar to search functions used in online shopping, not general internet searches.

Right out of the box, AI Search comes packed with cool features you can tailor to your needs. It can turn your relational data into JSON format, pick out key phrases, understand and use synonyms, handle geospatial data, and even detect and translate different languages, all without needing any extra services.

AI Search gets really smart with 'Skillsets' in its indexing pipeline. Think of it as giving your search engine some extra brain power. You can use these Skillsets to leverage other cool Azure AI services, Azure Machine Learning Models, custom AI endpoints, or even Microsoft's out-of-the-box search enhancements. It's all about making your search smarter and more tuned to your needs. And guess what? Setting it up is super easy – you can do it right from the Azure Portal or with just a bit of SDK code.

All this tech synergy is a two-way street (unlike my lopsided relationship with Pepé). While search-centric projects can be enhanced by AI, your planned and in-flight AI projects can be enhanced by adding rich search and retrieval capabilities. Let’s dive into three prime examples where your main AI projects could really get a lift from AI Search.

Three ways to boost your AI projects with Azure AI Search

1. Use AI Search Pipelines to combine search and knowledge mining applications

Now, I first want to say that AI Search is not a replacement for the likes of Azure Data Factory, or other ETL and ELT data processing solutions. AI Search simply doesn’t have all of the data connectors and optimization features of modern data management systems. That said, the AI Search knowledge mining architecture may just fit the bill for effective re-use of AI-enhanced data. 

In the basic AI Search architecture below, you can see where Skillsets (center-left) work to enhance the inbound data, and then pass it along to both the search index, as well as external knowledge stores and tooling, such as Power BI. This makes your AI-enhanced data available for both deep analytics and reporting, as well as interactive search by internal and external customers.

2. Use Azure AI Search for original source archives and research

Suppose you already have regulatory requirements to archive and catalog client contracts within your organization. You have leveraged Azure AI Services Optical Character Recognition (OCR) to help with the cataloging and have stored your documents in Azure Storage. Now, the marketing department believes they could really benefit from having the ability to use full-text search and other modern search capabilities over those client contracts. 

You could simply keep the current processing of new contracts in place and pull the documents in the existing knowledge stores into a separate search solution. But it’s also possible that it will be less expensive and easier to maintain by calling the OCR solution in a Skillset on your AI Search indexing pipeline — which could add additional enhancements to the data, beyond OCR — before sending it off to both the search index and the knowledge store or Power BI template.

3. Use Azure AI Search for translation projects

Imagine you are in the process of converting all of your online product assembly instructions into multiple languages. Maybe you are already using Azure AI Services to perform translations. But consider that if you integrated the translation functionality with AI Search language analyzers in order to make the instructions more easily searched by  both customers and service staff: the sum would be greater than the parts. 

Language analyzers from Lucene or Microsoft are used to intelligently handle language-specific linguistics including verb tenses, gender, irregular plural nouns, word de-compounding, word-breaking (for languages with no spaces), and more. It only makes sense to add Azure AI Search capabilities to your translation solution.

Scratching the surface: AI Search can do more for your projects

If, much like Pepé, you’re keen to pounce on what Azure AI Search can do for your AI projects, there’s actually a lot more than what I’ve listed above. Microsoft is continually enabling new AI-based integrations, including generative AI and deep learning applications. But to take advantage of those features, you’ll want to start with a solid foundation of knowledge around Azure AI Search. 

If you’re seeking to learn more about AI Search concepts and capabilities, I’ve put together a course on it: “Introduction to Azure AI Search.” The course also equips you with the skills and knowledge needed to configure, run, and monitor a basic Azure AI Search solution. If you’ve found this article helpful, I have a feline you’ll benefit from watching my course as well!