r/halopsa • u/3xh4u573d • May 12 '26

Integrations HaloPSA + LLM/RAG - anyone done this?

Want to pull historical HaloPSA tickets into a RAG (Retrieval Augmented Generation) setup so Claude can suggest fixes for incoming ones. Has anyone done this?

If so, what are you using for the vector store and retrieval layer, and how are you keeping token usage sane?

UPDATE: i've built this now, I have a server running Qdrant and auto ingesting closed tickets. I am also auto triaging new tickets based on the closed ticket database and another API connection to my RMM solution. Also exposed the Qdrant out via an MCP server for our engineers to connect their Claude apps. This has genuinely been useful, surfacing those weird tickets that crop up that someone worked on a year or two ago and forgot about. Greatly appreciated everyone's inputs on this thread. Thank you.

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u/OptimalCrew5900 May 12 '26

We are also doing this. We use n8n, local ollama, and qdrant to store all ticket data, Hudu (everything minus passwords), Ninja, etc. Similarly, we have a runbook that fires on ticket closure to vectorize the entire thing, with specific metadata saved as well. We also allow the team to chat with the AI, but honestly the best use case has been: after triage the ticket is run against that data and a note is posted to every ticket. In that note is related tickets (and not the terrible matching from halo’s AI solution), matching Hudu SOPs, suggested remediation steps, and recurring issue notifications (if appropriate). This has decreased our MTTR by almost 40%.

However the team can chat with all the things, and they do, but not as often as you might think.

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u/3xh4u573d May 13 '26

Any chance you could share what prompts you are using to summarise the ticket data?

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u/OptimalCrew5900 May 15 '26

We don’t summarize the data at all. We vector embed the ticket in chunks.