What challenges did RealTruck face before AI implementation?

Decades-old multi-brand systems and millions of vehicle-compatibility rows made it difficult to guide customers to the right accessories. Rigid configuration questionnaires and slow loading 3D assets created friction in the online shopping journey.

Source

GCPEvidence: Medium50/100

RealTruck Builder uses Gemini Enterprise Agent Platform for 3D accessory configuration

Use case typeDigital commerceUpdated Aug 6, 2026

RealTruck built a web-based 3D ecommerce experience to help shoppers identify the right truck accessories across a very large product catalog and complex vehicle-compatibility data. The application uses Gemini Enterprise Agent Platform, Gemini 3.1 Pro, Gemini 3.1 Flash Lite, Cloud Run, a Go backend, and a RAG pipeline to orchestrate AI responses and product reranking while visualizing accessories in 3D and augmented reality.

Organization: RealTruck
Industry: Automotive
Location: United States
Published: August 2026

Reported outcomes

Strategic outcomes

Competitive differentiationnew shopping differentiatorCustomer experience & trustrecreated a consultative store experience online

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Quantified impact: 10%

Google Cloud Customer StoriesAug 6, 2026Customer storyInferred claimMedium evidence strength

Captured roughly 10% of total website traffic with the new builder experience.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: RealTruck
Provider: GCP
Maturity: Unknown
Linked source: Google Cloud Customer Stories

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Digital commerce
2Product discovery
3Shopping recommendations

Built the RealTruck Builder WebGL application with Gemini Enterprise Agent Platform for orchestration.
Used Gemini 3.1 Pro for pre-processing and complex routing, Gemini 3.1 Flash Lite for fast customer-facing responses and reranking, and a RAG pipeline fed by compatibility trees, reviews, and category manager insights.

Technologies

Gemini Enterprise Agent Platform Gemini 3.1 Pro Gemini 3.1 Flash Live Cloud Run Go RAG WebGL

Improved customer confidence by showing products in virtual and augmented reality.

Architecture

A WebGL-based builder app routes requests through a Go backend to Google Cloud Agent Platform, where Gemini 3.1 Pro handles pre-processing and routing and Gemini 3.1 Flash Lite handles low-latency customer interactions; a RAG pipeline ingests compatibility trees, reviews, and category manager insights for product recommendations and visualization support.

Sources & evidence1

Evidence: Medium50/100Evidence strength