The best enterprise AI Search solution
Use Cases and Deployment Scope
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.



