Service-Knowledge Concierge | Real Minds AI
AutomotiveRetrieval (RAG)live

Service-Knowledge Concierge

Answers a technician or advisor's question from your own repair manuals, SOPs and right-to-repair data, with a citation for every answer — and says so when the answer isn't in the library rather than guessing.

apps.realmindsai.com.au/concierge · sandbox · read-only
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How it would work

One agent, grounded in your library, with citations on every paragraph.

01 · input
Member question
02 · agent
Your agent
03 · output
Cited answer or escalation
The problem it solves

Diagnostic and procedural knowledge stays trapped in a few senior technicians' heads and buried legacy folders. When junior staff hit an obscure fault code or part application, they interrupt a master tech or hunt across vendor portals — and Australia's right-to-repair scheme now gives independents dealer-level data that's hard to operationalise quickly.

This pattern ingests repair manuals, SOPs, technical bulletins, and historical repair orders into a secure, searchable store inside your tenancy, then answers questions in plain English with an exact citation for each answer. When the answer isn't in the library it says so and escalates, rather than inferring — improving first-time-fix rates and easing pressure on senior staff.

TA
Tracy Anthony · Co-Founder & CEO · wrote up this design
What it would take to build

Estimated build: 3–5 weeks. Most of it is template work we've already done.

Estimated build time
3–5weeks
Diagnostic · build · soft launch · review.
Reused from template
~70%
Agent shell · retrieval · audit · deployment.
Bespoke to this skin
~30%
Document ingestion, citation and grounding rules.
stack · private RAG · vector store · LLM
What it would cost for your org

Fixed scope, fixed price, fixed dates.

The cost band reflects the engagement shape, not a per-feature line item. We work on fixed scope, fixed price, fixed dates — see the services catalogue for what falls inside each band.

Engagement band
A bite-sized first piece → pilot build → embedded support. Start small, scale on proof — most builds land in the pilot band.

Considering this for your org?

The honest place to start is a bite-sized first piece — one contained change, low risk. Tell us where it hurts; we’ll play it back, scope it, and show you what’s possible.

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