Cars24 внедрила голосовых и чат-агентов OpenAI: 1 млн минут диалогов и возврат 12% лидов

The Indian auto marketplace Cars24 has shifted its customer communications to voice and chat agents built on OpenAI models: the bots handle more than 1 million minutes of conversations per month and help recover 12% of lost leads. The case study was published on the OpenAI blog in July 2026.

How Cars24 uses OpenAI agents

Voice and chat agents built on OpenAI models handle the main flow of customer communications at Cars24 — more than 1 million minutes of conversations every month. That volume — over 16 thousand hours of dialogue per month — is comparable to the full workload of a call center of roughly a hundred operators. Cars24 is a platform for buying and selling used cars, founded in 2015 in India; the deal here is expensive and long, so the speed and quality of responses directly affect revenue. The agents answer buyers' questions, help sellers with car valuations, and bring back into the funnel customers who did not complete their applications.

Key figures from the case study, according to the OpenAI blog:

• More than 1 million minutes of conversations per month are handled by the voice and chat agents
• 12% of lost leads are recovered by Cars24 through automated communications
• Agentic workflows are being deployed in teams across the entire company, not only in support
• Cars24 has operated in the used car market since 2015

Why recovering 12% of leads matters

Recovering 12% of lost leads for an auto marketplace means a direct revenue increase without a larger advertising budget. A lost lead is a customer who submitted an application but did not answer a call or abandoned the process halfway; in a traditional call center, such applications often never get followed up. A voice agent, unlike a human operator, calls back thousands of customers simultaneously, at a time convenient for them and without queues on the line.

The economics of voice agents in the auto business are more visible than for most chatbots: a car deal is measured in thousands of dollars, so even a few percent of recovered applications pay for the implementation. In the case study, Cars24 links the agents specifically to recovering lost demand, not just to cutting support costs.

What the agentic approach gives the company

Agentic workflows at Cars24 go beyond customer support: according to the OpenAI blog, the company is deploying them in teams across the entire organization. The company calls these agentic workflows. In such a process, an agent does not simply answer a question but performs a chain of actions: it finds data, triggers the next step, and hands the result over to a human.

"Cars24 uses voice and chat agents powered by

OpenAI to handle more than a million minutes of conversations per month, recover 12% of lost leads, and deploy agentic processes in teams across the entire company," the case study on the OpenAI blog says.

The phrase "builds faster" in the case study's headline refers not only to the service: Cars24's internal teams use OpenAI tools to assemble workflows and internal products faster. This is a typical second stage of enterprise adoption — first front-line automation, then moving agents into internal operations.

What this means

Voice AI agents are no longer an experiment: at Cars24 they operate at a scale of a million minutes per month in a business built around an expensive purchase — a car. For companies with a large flow of applications, the benchmark is simple: measurable returns come not from a "chatbot on the website" but from an agent embedded in the sales funnel that brings back lost customers. Case studies of this scale also show where OpenAI is steering the enterprise segment — from one-off pilots to agents in daily operations.