Six jobs. Six specialized models.
Azure AI Foundry pairs each business problem — search, images, video, claims, calls — with the model actually built for it.
What you'll learn
- Which Azure AI Foundry model fits which business problem — embeddings, image and video generation, vision, and speech.
- Why semantic search beats keyword search for real customer questions.
- How a multimodal model and speech models turn a photo or a phone call directly into structured, actionable data.
Share this passage
Drawing…
Understand it one step at a time
The short runs these in order in about 25 seconds. Here they are written out — pick any step to jump the short straight to it.
Can one model handle six different jobs?
No. Search, images, video, claims and calls each need a different kind of model.
Frequently asked questions
- Why does semantic search find a policy that shares no words with the question?
- Embedding models like Ada and Cohere convert both the question and the documents into vectors that represent meaning, not exact text. "Can I return shoes that got wet in the rain?" and "items damaged by weather are refunded in full" share zero keywords but sit near each other in vector space, so the match still surfaces — a keyword search would return nothing.
- Can one Azure AI Foundry project really cover search, images, video, claims, and support calls?
- Yes. Embeddings, GPT-image-1, Sora 2, GPT-4.1, and the GPT-4o transcribe/tts pair are all separate task-built models sitting in the same catalog under the same project, so one team's Foundry setup can back retail search, marketing creative, claims triage, and voice support without standing up separate infrastructure for each.
Free app · no app store
These are built for a phone
Every short is drawn at full portrait height, the shape a phone already is. Installed, it opens full-bleed with no address bar across the top — and the whole library reads offline.
Read deeper on Azure
Twenty seconds gets the shape of an idea across. These go into how it behaves in production.
-
Azure AI Foundry Model Catalog: How to Choose the Right Model
A decision framework for the Foundry model catalog: LLMs vs SLMs, chat vs reasoning models, and specialized models, with real business use cases.
-
AI Bot Attacks on a Mobile App Login, and How Azure Stops Them
A script tries 8,000 passwords a minute against your login API at 3am. Rate limiting, smart lockout and Defender for Cloud make speed the losing move.
-
Azure Key Vault Explained: The One Secret Tutorials Never Remove
Moving every secret into Key Vault leaves exactly one behind: the credential that opens the vault. A managed identity is what removes it.
More shorts
-
Azure
One tap. Two orders.
10 steps · 57s
-
Azure
1.6 million downloads. One photo.
10 steps · 58s
-
Azure
Your public API has no login — and no identity
8 steps · 26s
Get new posts by email
New technical articles, Azure AI and GitHub Copilot updates, and upcoming events. No spam, unsubscribe anytime.
MSDEVBUILD
/ blog Multi-Stack Dev Build · by Suthahar Azure