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Azure AI Search

Score8.8 out of 10

31 Reviews and Ratings

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What is Azure AI Search?

Azure AI Search (formerly Azure Cognitive Search) is enterprise search as a service, from Microsoft.

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Who Buys & Uses Azure AI Search

Azure AI Search Reviews

What users are saying about Azure AI Search.
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Azure AI Search for document accurate search

Kharan Raju
Data Scientist in Information Technology at Intellectyx Inc (51-200 employees employees)

Use Cases and Deployment Scope

We use Azure AI Search in our organization to bring relevant chunk text from our database postgres pgadmin vector db for our chatbot based model. Based on the user query, by using the retrieval mechanism connect with Azure AI Search ranking and relevant text will be retrieved from the database to answer the user query from our trained document.

Pros

  • Relevant query text finding the answer from the chunk text
  • Accurate output for the chatbot it works well
  • Faster response it works well

Cons

  • If the data is larger or heavy there it have to work
  • If the data is larger accuracy should be improved
  • Large data handling time also important thing to work faster

Return on Investment

  • It always meet our expectations
  • 25-25% time it is saving
  • cost wise little higher

Usability

Other Software Used

pgAdmin, Postman, Cursor

The best enterprise AI Search solution

Incentivized
Parth PuraniView profile
Lead Cloud Engineer in Engineering at Civica (1001-5000 employees employees)

Use Cases and Deployment Scope

Azure AI Search is heavily being used by our file management system to search and retrieve items based on search token provided. The Azure AI Search is very versatile in working with multiple sources of data and ability to integrate with Chat Bot is very handy. The implementation is very easy and seamless.

Pros

  • The Azure AI Search has all state-of-the-art LLM models ready to use for our enterprise grade apps.
  • Azure AI Search seamlessly integrates with our Azure infrastructure and provide most advance security for our sensitive data.
  • It's hybrid search ability makes it much faster than the conventional search algorithm which would require us to index the database.

Cons

  • Azure AI Search formerly known as Cognitive search has very limited development SKU model for getting started which makes it costly while just getting started.
  • We had an issue with limited file size capped at 16Mb, which turned into a system wide limitation for our product since many of our blobs exceeded the 16Mb mark.
  • For larger systems the REST rate limits for the query API can become a headache if you don't plan for possible influx of peak requests.

Return on Investment

  • When integrated with our existing file system the Azure AI Search helped users tremendously by reducing search times and improve efficacy of intended result.
  • Since Azure AI Search is a PaaS solution, we had very short ideation to go-live timespan, which ended up reflecting in our product performance.
  • A rare but not negligible occurrence was correctness of search being questionable when new data was added to the system. The search returns false positive results.

Usability

Alternatives Considered

Elasticsearch

Other Software Used

Azure App Service, Azure Kubernetes Service (AKS), Azure SQL Database, Azure Files, Azure Container Registry, Azure Private Link, Azure Monitor, Azure Virtual Network

Get results exactly you need.

Incentivized
Verified User
Analyst (11-50 employees employees)

Use Cases and Deployment Scope

I can search for any type of data, such as images, audio, and multilingual text, as well as large, complex datasets. It saved my time, and it is really a fully intelligent AI that has more problem-solving skills than other AI models, and I get the exact answer to any data

Pros

  • Takes very complex data.
  • Get any type of data that you need at right time.
  • Filters are very good to search for data.

Cons

  • The free plan storage is very low for anyone who want to lean azure AI search.
  • The plan is too high for me.
  • They need to intricate ai search is every Microsoft ecosystem.

Return on Investment

  • Organizations need to train employee to use this.
  • The Azure search feature is good for data analyst and big data type job.
  • Azure ai search is very intelligent they can read large amount of data in few minutes.

Usability

Alternatives Considered

Cisco Cloud Web Security

Other Software Used

Azure AI Search, Azure Cloud Services

Azure AI Search: Market leader in this segment

Incentivized
Verified User
Manager in Information Technology (501-1000 employees employees)

Use Cases and Deployment Scope

Azure AI Search is increasingly being utilized in the TV broadcast industry which address various challenges and enhance content delivery and management. We uses it for content creation and disribution. This helps us in managing workflows, quick dicision making , timely delivery of projects. This helps us to understand audience preferences , based on this content is being created considering individuals mood and interest.

Pros

  • Content recommendations, AI recommends shows and content as per viewer preferences , which enhances user experience.
  • This helps in managing workflows which makes decision making easier and time delivery of project.
  • with the help of Generative AI, it increased scalability of all AI applications.

Cons

  • Cross platform compatibility to integrate with various OS
  • Optimizing latency.
  • Nothing better than work on price, create more flexible options.

Return on Investment

  • Service cannot be downgrade or upgrade after creation
  • Good tool provide maximum ROI

Alternatives Considered

Amazon Augmented AI (Amazon A2I)

Other Software Used

Adobe Analytics, Amazon API Gateway, Microsoft 365

Great search software for an enterprise organization

Incentivized
Blake BaronView profile
Ecommerce & Consumer Products Manager in Sales at Midwest Tungsten Service (11-50 employees employees)

Pros

  • Incredibly robust back-end infrastructure.
  • Streamlined integration into Microsoft's Azure Cloud.
  • From a user standpoint, it lets the customer easily access their data and provide useful search tips.

Cons

  • It's an enterprise level product so you need to have the budget for it.
  • Challenging-to-impossible for a non-technical administrator to implement.
  • It further locks you into Microsoft's ecosystem and doesn't play well with non-Microsoft software. Depending on your point of view, this can be a pro or a con.

Return on Investment

  • Our internal market research illustrates that users are finding their desired information faster on account of autosuggest.
  • Time spent on checkout page (for conversions) is significantly decreased.
  • Clicks required on checkout page (for conversions) is significantly decreased.

Alternatives Considered

Google Cloud AI

Other Software Used

Microsoft Azure, BigCommerce, Sage 50 Accounting