Tata Motors turned an underutilized digital lead funnel into $10M+ in new sales, increasing conversion by 4× partnering with Hyde. In parallel, Tata Motors also built a custom Speech-To-Text model trained on Indic languages and real-world sales workflows.
Context
Tata Motors, a $50B+ global automaker, generates over half a million digital leads every month across its online channels. But its human sales team weren’t built for that scale, converting a small fraction of digital leads and leaving a massive pool of unrealised demand.
Previous attempts to automate the workflow with CRM-based RAG systems failed at different points. Off-the-shelf speech models struggled with the complexity of the Indian market: dozens of Indic languages, strong regional accents, multilingual conversations, and highly technical automotive terminology. Latency also proved to be a major barrier as conversations needed to feel natural for voice agents to work in real customer interactions.
Tata Motors also required full enterprise ownership of the final system, with all models trained and deployed on-premises using proprietary data.
Solution
Tata Motors is building and deploying specialist models and AI voice agents to transform the company’s digital customer sales.
Instead of relying on generic models, Tata Motors developed a custom AI stack trained on their proprietary datasets and real customer interactions.
For the STT model, the foundation was a fine-tuned speech recognition system optimized for Indic languages. This involved deploying a custom VAD and Parakeet-0.6B speech-to-text models trained on 10 years of Tata Motors call center conversations, enabling accurate recognition of regional accent and specific automotive terminology.
In addition to this, Tata Motors and Hyde built custom reasoning models trained on more than 25 years of CRM and DMS datasets. These models generated a personalized sales thesis for every lead, identifying the likely intent of purchase. Leads are scored and routed to the most effective outbound channel, while the custom model determines the next best action. Feedback from the action is fed back to the system to retrain and refresh embeddings, improving the precision of the model.
Additionally, the specialist model generated simulations of customer profiles to optimise marketing and merchandising decisions.
Together, these systems power real-time agents capable of engaging in outbound marketing, qualifying leads, answering product questions, recommending vehicles, and routing high-intent buyers to dealerships.
Impact
By transforming how Tata Motors engaged with its digital lead funnel, Hyde helped the company increase it digital sales conversion rate by 4x in the pilot phase alone. This translated to $10M+ in directly attributable vehicle sales from leads that previously went unaddressed.
Tata Motors’ custom speech-to-text model built with Hyde is the world’s best across Indic languages, outperforming state-of-the-art speech models by 10× across accuracy, latency, and cost.
Because the models were built for enterprise ownership and on-premise deployment, they are now being deployed across the broader Tata ecosystem as a strategic asset - extending into post-sales engagement, customer support, and supply chain operations.
Takeaway
Scaling AI in production requires more than general-purpose models. It requires systems deeply embedded in enterprise data, optimized for real-world constraints, and continuously improved through operational feedback. Tata Motors is leapfrogging its competitors by investing deeply in this foundational layer.
