One assistant replaced search and support across three business units, raising click-through 14%.
Lexus Europe AI Concierge
Call to action clicks rose 274% and lead conversions 190%, with more configurations completed.
A concierge that answers in natural language, picks its own response format, and drives a real-time color selector.
What the agent does
Answers a buyer question, picks its own response format, drives a real-time color selector and routes to a test drive or a dealership.
- Brand
- Lexus Europe
- Contributed by
- Valtech (Systems integrator)
- Industry
- Automotive
- Audience
- B2C
01
The problem
Why this exists
Buying a premium car online is a research task spread across model pages, specification tables, configurators, and dealer locators, and each of those answers a different question in a different format.
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A recommendation engine does not solve this. It predicts which vehicle a visitor is likely to want from past behavior, when the visitor's actual question is a comparison, a specification, or how to book a test drive, and none of those have a single right answer shape.
02
Outcomes
What changes when this is in place
- 274% increase in call-to-action clicks.
- 190% increase in lead conversions.
- 41% increase in completed vehicle configurations.
Read more
- Visitors are guided to meaningful next steps: model pages, test drive bookings, and dealership finders, rather than left in the conversation.
03
How it works
Architecture
The concierge understands natural language queries from prospective and returning customers, then pulls relevant knowledge from multiple Lexus data sources through retrieval-augmented generation rather than from a single indexed source.
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The distinctive part is presentation. The concierge dynamically selects the best response format for the answer, choosing between comparisons, tables, and lists, so a specification question and a comparison question do not come back in the same shape. A real-time color selector is integrated into the conversation for vehicle visualization.
It operates under strict guardrails for data privacy and brand tone of voice, which for a premium automotive brand is a delivery requirement rather than a preference.
Valtech positions this against a standard recommendation engine: rather than predicting a vehicle from behavior, the concierge interprets intent in context, synthesizes knowledge from several sources, decides how to present it, and guides the journey in real time.
Open standards used
REST APIs
Tech stack
Retrieval-augmented generationReal-time color selectorLexus knowledge sources
Resources
Next step
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Everyone credited on this solution
- ValtechSystems integrator
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Verification
Published case study
The detail on this page is drawn from a case study published by the contributor or the MACH Alliance. Any figures on this page are the ones that case study states.
Where this came from
Solution detail is published from the contributor's 2026 Agent Ready submission to the MACH Alliance. Submitter names and contact details are not published.
Status: Live in productionAdded Jul 8, 2026A listing is an editorial decision, not a MACH Alliance certification.
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