How Cars24 scales conversations and builds faster with OpenAI

Details

OpenAI published a case study on Cars24, an Indian used-car marketplace, which deployed voice and chat agents powered by OpenAI to manage customer conversations at scale. The headline metrics: over 1 million conversation minutes handled monthly and a 12% recovery rate on leads that previously went cold. The deployment spans both customer-facing and internal workflows. On the customer side, voice and chat agents handle the high-volume top-of-funnel conversations that human sales teams find too expensive to cover at this scale. Internally, agentic workflows are described as enabling teams across the company to build and iterate faster, though the excerpt does not specify which teams or workflows. The business context matters: Cars24 operates in a market with high conversational volume and significant cost pressure. Automating initial customer contact at scale while recovering a meaningful percentage of lost leads represents a direct revenue impact that is easier to quantify than many AI deployments. The source content is limited to a brief description—full technical details on architecture, implementation timeline, model configuration, and additional performance metrics would require reading the complete OpenAI case study.