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How is Toma transforming auto dealerships with Monik Pamecha

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Conteúdo fornecido por Rohit Malhotra. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Rohit Malhotra ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

Today I am excited to have Monik Pamecha who is one of the co-founders of Toma, helping auto dealerships automate phone calls with AI. Toma offers AI agents that can autonomously handle phone calls, provide a natural voice experience, design call flows, integrate with existing software, and perform tasks on and off calls.

In this episode Monik Pamecha, co-founder of Toma, leveraging AI to enhance customer calls for auto dealerships shares his journey from India to the US, his early fascination with technology, and the transformative impact of Y Combinator on his entrepreneurial path. Monik elaborates on Toma’s pivot to focusing on the auto dealership industry, the challenges faced, and the rapid traction gained. Monik also provides insights into the future of AI in customer service, its impact on the BPO industry, and essential advice for early-stage startup founders, and much more!

Subscribe on Spotify

Subscribe on YouTube

Subscribe on iTunes

Learn

* Why did Monik decide on a specific niche in auto dealerships

* What approaches are used to design and manage the AI call flows and agents?

* How does Toma ensure transparency that customers are interacting with an AI agent?

* What is your favourite business book? – Zero to One

* What is your favourite online tool? –Jira

* If you could go back to when you started working, what is the one thing you would have focused on? – Be bolder

Timestamps

6:15 - Comparison between New York and San Francisco tech scenes.

8:45 - Overview of Y Combinator's philosophy and process.

12:15 - Pivoting during YC and the support for such changes.

13:30 - Finding a product-market fit in auto dealerships.

15:00 - Initial traction and customer feedback.

17:45 - Regulations and business dynamics in the automotive industry.

19:00 - Onboarding first customers across various states and brands.

21:30 - Developing natural-sounding voice interactions and product iterations.

23:30 - Metrics for judging call performance and business impact.

24:45 - Potential impact of AI on the BPO industry in India and the Philippines.

27:30 - Addressing AI bias and design solutions for inclusivity.

Monik’s Links

LDN– https://www.linkedin.com/in/monikp/

Website – https://tomato.ai/

My Links

Podcast: https://lifeselfmastery.com/itunes

YouTube: youtube.com/lifeselfmastery

Twitter: https://twitter.com/rohitmal

5-day email course: www.enterprisesalesexpertise.com

Newsletter:


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit partnergrow.substack.com
  continue reading

227 episódios

Artwork
iconCompartilhar
 
Manage episode 432013997 series 1580277
Conteúdo fornecido por Rohit Malhotra. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Rohit Malhotra ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

Today I am excited to have Monik Pamecha who is one of the co-founders of Toma, helping auto dealerships automate phone calls with AI. Toma offers AI agents that can autonomously handle phone calls, provide a natural voice experience, design call flows, integrate with existing software, and perform tasks on and off calls.

In this episode Monik Pamecha, co-founder of Toma, leveraging AI to enhance customer calls for auto dealerships shares his journey from India to the US, his early fascination with technology, and the transformative impact of Y Combinator on his entrepreneurial path. Monik elaborates on Toma’s pivot to focusing on the auto dealership industry, the challenges faced, and the rapid traction gained. Monik also provides insights into the future of AI in customer service, its impact on the BPO industry, and essential advice for early-stage startup founders, and much more!

Subscribe on Spotify

Subscribe on YouTube

Subscribe on iTunes

Learn

* Why did Monik decide on a specific niche in auto dealerships

* What approaches are used to design and manage the AI call flows and agents?

* How does Toma ensure transparency that customers are interacting with an AI agent?

* What is your favourite business book? – Zero to One

* What is your favourite online tool? –Jira

* If you could go back to when you started working, what is the one thing you would have focused on? – Be bolder

Timestamps

6:15 - Comparison between New York and San Francisco tech scenes.

8:45 - Overview of Y Combinator's philosophy and process.

12:15 - Pivoting during YC and the support for such changes.

13:30 - Finding a product-market fit in auto dealerships.

15:00 - Initial traction and customer feedback.

17:45 - Regulations and business dynamics in the automotive industry.

19:00 - Onboarding first customers across various states and brands.

21:30 - Developing natural-sounding voice interactions and product iterations.

23:30 - Metrics for judging call performance and business impact.

24:45 - Potential impact of AI on the BPO industry in India and the Philippines.

27:30 - Addressing AI bias and design solutions for inclusivity.

Monik’s Links

LDN– https://www.linkedin.com/in/monikp/

Website – https://tomato.ai/

My Links

Podcast: https://lifeselfmastery.com/itunes

YouTube: youtube.com/lifeselfmastery

Twitter: https://twitter.com/rohitmal

5-day email course: www.enterprisesalesexpertise.com

Newsletter:


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit partnergrow.substack.com
  continue reading

227 episódios

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