Case Studyragvoice assistantmongodb atlasvoyage 3 large
Mechanic Shop Deploys AI Receptionist Axle
6.2
A developer built Axle, an AI receptionist for his brother’s mechanic shop to answer customer calls and capture callbacks in real time. The system uses a RAG pipeline with 21+ scraped documents embedded by voyage-3-large into MongoDB Atlas, Anthropic Claude for grounded responses, and Vapi (Deepgram/ElevenLabs) for telephony and voice synthesis. It logs calls, escalates unknown queries, and aims to reduce missed revenue.
Key Points
- 1Implements RAG-backed voice agent using Voyage embeddings and Claude to answer grounded customer queries
- 2Reduces lost revenue by preventing hallucinated pricing and preserving leads through callback logging and escalation
- 3Enables small businesses to automate phone intake with MongoDB vector search, Vapi telephony, and voice tuning
Scoring Rationale
Practical, well-documented implementation provides reusable RAG+voice patterns; limited by single-shop scope and anecdotal single-source reporting.
Sources
Public references used for this report.
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