Auto Dealers/Service Providers: From "Sales Consultants Overwhelmed"
to "AI Sales Consultant + AI After-sales Technician"

Enterprise AI Workstation can host a complete vehicle parameter knowledge base (covering 10+ models on sale × 50+ technical parameters), so sales consultants don't need to memorize everything. When customers inquire, AI retrieves vehicle configurations, competitor comparison data, financial plan recommendations, and other information in real-time to assist sales consultants in providing professional answers. Field data shows that test drive booking conversion rates increase by an average of 35%+, and new hires with just 3 days on the job can reach the professional level of 3-year veterans. For more details, please visit the Products page.

Trained on massive OBD fault code libraries and repair case databases, the AI after-sales technician can quickly locate fault causes and recommend repair solutions. It supports parts query matching, labor hour estimation, maintenance item recommendations, and other features. After-sales technician training cycles are compressed from the traditional 2-3 years to 3 months, significantly reducing dependence on senior technicians. For specific feature mapping, refer to the "Feature Mapping Table" section above, or Contact for a detailed solution.

Enterprise AI Workstation supports unified multi-channel access—the official website, WeChat Official Account, Enterprise WeChat, APP embedded, phone voice, and all other channels share the same knowledge engine. Inquiries initiated by vehicle owners in the APP seamlessly connect with the Official Account side, with zero loss of nighttime leads (consultations after 8 PM account for over 30%). All conversation records are uniformly deposited into the CRM/DMS system to form a complete customer profile. For more access methods, see the Products - Multi-channel Access module.

The system automatically calculates the optimal maintenance timing based on vehicle information (brand, model, mileage, last maintenance time) and owner profiles, and reaches out through multiple channels (WeChat/SMS/APP push). It supports one-click appointment scheduling and automatically synchronizes with the store's scheduling system. After implementation, the after-sales return rate increases by 25%, and secondary marketing conversion rates such as insurance renewal and trade-in also improve synchronously. This feature is one of the core modules of the "Full Lifecycle Proactive Outreach" solution.

Yes. Enterprise AI Workstation structures all brand vehicle parameters, configurations, and pricing data into a knowledge graph, supporting natural language Q&A queries. For example, if a user asks "How much longer is this car's wheelbase compared to competitors?" or "Which configuration has L2-level assisted driving?", AI can provide precise comparison results within 1 second. The knowledge graph is continuously updated as new vehicles are launched, ensuring information is always accurate. This feature is already a core usage module; see the "Knowledge Engine" row in the feature mapping table above for details.

AI can answer high-frequency consultation questions such as insurance policy interpretation, claims process guidance, required document lists, and claims progress inquiries. It includes built-in financial tools such as loan calculators, leasing plan generators, and trade-in valuation models, outputting optimal financial plan combinations with one click based on customer needs. Financial plan explanation time is reduced by over 60%, freeing up more time for sales consultants to communicate with high-value customers. If you need a customized financial knowledge base, please contact the pre-sales team for evaluation.

Supported. It includes a built-in used car valuation model that combines multiple dimensions of data such as vehicle age, mileage, condition grade, and market trends to provide owners with reference valuation ranges. It can also link with trade-in recommendation logic, proactively triggering outreach when it detects that a vehicle has reached the optimal trade-in timing. For dealer groups operating used car businesses, this feature can be directly embedded as an online valuation tool, significantly improving online inquiry-to-store conversion rates. For specific pricing plans, see the Pricing page.

Enterprise AI Workstation adopts a multi-tenant architecture design, supporting flexible modes of unified group-level control + independent knowledge bases for each brand/store. The group can set unified brand script standards while allowing each 4S dealership to fine-tune according to localization needs. Data permissions are strictly isolated, and each brand's data is invisible to others. It has served multiple national automotive dealer groups, covering mixed operation scenarios of luxury brands and mass-market brands. For case details, browse the Cases page.

Based on actual operational data from deployed automotive customers: test drive booking conversion rate +35%, after-sales return rate +25%, technician training cycle compressed from 2 years to 3 months, unlimited AI memory capacity for vehicle parameters. Usually, obvious results can be seen 2-3 months after deployment, with an investment recovery cycle of about 6-8 months. ROI calculations vary for dealers of different sizes. It is recommended to Contact for a customized ROI analysis report for your enterprise.

The standard implementation cycle for the automotive industry is 2-3 months, divided into four phases: ① Week 1-2 knowledge collection (collect vehicle materials, fault code libraries, script documents); ② Week 3-4 knowledge training (clean and annotate data, train industry-specific models); ③ Week 5-7 system integration (integrate with CRM/DMS systems); ④ Week 8-10 grayscale optimization followed by full go-live. If you already have a solid digital foundation (DMS/CRM), it can be compressed to as fast as 6 weeks. Get started now: 7-day free trial.