AI agents for automotive dealerships

Toma is an AI-powered voice agent platform designed specifically for automotive dealerships. It automates inbound customer communications by answering calls, scheduling service appointments, qualifying leads, and routing complex inquiries to the appropriate staff members. The system integrates directly with existing dealership management systems (DMS) and service schedulers, ensuring seamless operation within current workflows.
Targeted at automotive service departments and dealership managers, Toma addresses common operational challenges such as missed calls, inefficient customer follow-up, and high advisor workloads. By handling routine interactions, the platform allows human teams to focus on higher-value in-person customer engagements while maintaining consistent communication standards across all channels.
Toma operates by intercepting incoming calls to a dealership's phone lines and engaging callers using natural language voice AI. The agent identifies caller intent—such as service scheduling, parts inquiries, or general information—and either resolves the request autonomously or initiates a transfer to the appropriate department. For service appointments, it accesses vehicle history and manufacturer recommendations to suggest suitable maintenance plans and available time slots.
When a call requires human intervention, Toma attempts to connect the customer to the relevant advisor. If the transfer fails, the AI automatically re-engages the caller (transfer clawback), collects necessary details, and routes the inquiry elsewhere. After each interaction, complete transcripts, sentiment analysis, and outcomes are logged in a unified dashboard called Inbox, where team members can review, assign, and respond to pending actions.
Dealerships use Toma to improve customer satisfaction scores (CSI) by ensuring timely responses and reducing wait times. The automated service scheduling feature captures revenue opportunities that might otherwise be lost due to missed calls or understaffed front desks. Service departments benefit from reduced administrative load, allowing advisors to dedicate more time to in-store customers.
The system also enhances internal efficiency through features like automated appointment reminders via text and voice, which decrease no-show rates and optimize bay utilization. Dropped call recovery ensures that even accidental disconnections lead to continued engagement. With follow-up alerts and a centralized conversation log, managers gain visibility into customer touchpoints, enabling better coordination and accountability across teams.