By Admir Sahbaz,
Principal @ Authority Partners
June 4, 2026
An AI agent’s ability to deliver accurate, relevant responses depends on more than the language model itself. The quality of the retrieval layer, how information is indexed, searched, and ranked, plays a critical role in ensuring outputs remain grounded in trusted source data.
In this session, Admir Sahbaz, a solution architect, walks through the full Azure AI Search retrieval stack: from data ingestion pipelines and integrated vectorization through hybrid search, semantic re-ranking, query rewriting and agentic retrieval. By the end, you’ll have a clear picture of how these components work together in Azure AI Search to deliver high-relevance grounding for AI agents.
Principal, Authority Partners
Admir Sahbaz is a software architect with over 10 years of experience building enterprise-grade software solutions end to end, from architecture and design to implementation and deployment. He has extensive experience within the Microsoft ecosystem, specializing in .NET and Azure, and has successfully applied these technologies across a wide range of client engagements. Admir is enthusiastic about architecture, cloud and DevOps, and enjoys staying hands-on while supporting teams in building high-quality solutions.
Explore the limitations of traditional Retrieval-Augmented Generation (RAG) approaches and see how advanced retrieval techniques can improve performance when handling complex, multi-step, and ambiguous user queries.
Duration: 75 minutes | Recorded live | Free to access
Thoughts, breakthroughs, and stories from the people building what’s next.
We’re here to help!
Let’s make sure we put you in touch with the right people! Let us know what you’re interested in.
Not ready for a call yet?
Send us a note and we'll reach out to you.
Ready to talk?
Pick a time.
Not ready for a call yet?
Send us a note and we'll reach out to you.
Ready to talk?
Pick a time.
