Azure AI Search vs. Netcore Unbxd

It's very useful when used with large file systems, once the models index the files good enough, the suggestions are very impressive and produce grounded answers. Since it can natively work with blob storage the requirement for pre-processing the data is eliminated i.e. the data can be searched in its raw form, this makes Azure AI Search a very powerful tool when used with Azure Stack.

Incentivized

Best scenarios: To explain to the customers how the product works in searching any operation and to give the demo to customers. Less appropriate: To describe the customers in a very short span of time.

• 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.

Incentivized

• Auto suggest widgets
• Visual workbench
• A/B testing

• Like virtually all Azure services, it has first-class treatment for .Net as the developer platform of choice, but largely ignores other options. While there is a first-party Python SDK, there are only community packages for other languages like Ruby and Node. Might be a game of roulette for those to be kept up-to-date. This might make it a non-starter for some teams that don't want to do the work to integrate with the REST API directly.
• In my opinion, partitions inside of Azure Search don't count as data segregation for customers in a multi-tenant app, so any application where you have many customers with high-security concerns, Azure Search is probably a non-starter.
• To elaborate on the multi-tenant issue: Azure Search's approach to pricing is pretty steep. While there is a free tier for small applications (50MB of content or less) the first paid tier is about 14x more expensive than the first SQL Database tier that supports full-text search. For many applications, it makes a lot more economic sense to just run some LIKE or CONTAINS queries on columns in a table rather than going with Azure Search.

Incentivized

• Animated toons
• Some short video explanations
• Fast and ready suggestions

I want to improve their product and also want to learn Azure AI Search like a professional and use it with full feature but their price is too high, so now I use the free plan as of now, but it takes a very large amount of data, type is few minutes, and give result that I want.

Incentivized

Product enhancement and recent updates, Azure AI Search has become more cost-effective, especially for large-scale generative AI applications2.

Incentivized

They have some good graphics and displays for overall reports. Reports and data analytics reports are having good insights into all the data. The reports are enough to calculate each time series analysis.

• 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.

Incentivized

• Positive impact: Reports , Speed of report generation.
• Negative feature: AI feature : sometimes it didn't work.