Automation library · Customer support

Build an AI IT support agent with Azure Search and Entra ID

Started by someone opening a chat with it. It calls services over plain HTTP rather than through connectors. It puts Gemini behind a retrieval step, so answers are drawn from documents you supply rather than from the model alone. 26 steps: large, and worth reading before you trust it with anything live.

LargeCalls a model: GeminiRetrieval

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26 stepsLarge: read it before trusting it with anything live
0Branches: places the flow splits
0Loops or waits
0Services by connector: it calls them over plain HTTP

The flow

Starts it 4Model 3Logic 5Service 14

The steps in the order they run, from what starts it.

  1. 1When chat message receivedChat triggerStarts it
  2. 2Google Gemini Chat ModelLm Chat Google GeminiModel
  3. 3Simple MemoryMemory Buffer WindowModel
  4. 4Create Jira TicketJira ToolService
  5. 5On Knowledge UploadForm triggerStarts it
  6. 6When clicking ‘Test workflow’Manual triggerStarts it
  7. 7Semantic SearchWebhookStarts it
  8. 8Invoke Query Vector Store WebhookHttp Request ToolService
  9. 9Reset User PasswordHttp Request ToolService
  10. 10Query Microsoft Entra ID UsersHttp Request ToolService
  11. 11Set Common Fields2SetLogic
  12. 12IT Support AgentAgentModel
  13. 13Split Out Binary FilesSplit OutLogic
  14. 14Set Common FieldsSetLogic
  15. 15Get Embeddings1Http RequestService
  16. 16Prep ContentCodeLogic
  17. 17Create Azure AI Search ServiceHttp RequestService
  18. 18Get Azure AI Search Admin Key2Http RequestService
  19. 19Get EmbeddingsHttp RequestService
  20. 20Enable Semantic SearchHttp RequestService
  21. 21Query Azure AI Search IndexHttp RequestService
  22. 22Set Common Fields1SetLogic
  23. 23Get Azure AI Search Admin KeyHttp RequestService
  24. 24Get Azure AI Search Admin Key1Http RequestService
  25. 25Create Azure AI Vector IndexHttp RequestService
  26. 26Upload Embedding to Vector StoreHttp RequestService

How it's built

Starts on
Someone opening a chat with it
Steps
26
Size
Large: read it before trusting it with anything live
Connects to
Nothing by connector; it calls services over plain HTTP
Model
Gemini
Retrieval
Answers are drawn from documents you supply, not from the model alone

Questions

What does it need to run?

An n8n account, and a key for Gemini. You connect your own accounts after importing it; none are included.

What starts it?

It starts on someone opening a chat with it.

Does it use AI?

Yes. It calls Gemini. Its answers draw on documents you give it, not on the model alone. Model calls are billed by the provider, not by n8n.

How long does it take to set up?

Take your time. At 26 steps it is large: read it before trusting it with anything live.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

Before you run it

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 26 steps before you point it at anything that matters.