More about Nisarg Pandya
Nisarg Pandya is the founder and CEO @drivebuddyAI - An AI & Telematics arm of Roadzen. DrivebuddyAI was founded in 2018 by Nisarg Pandya and later acquired by Roadzen Technologies in 2019.
Nisarg has been an entrepreneur and driving the growth of drivebuddyAI since the inception. He is an engineer entrepreneur and started the product building at drivebuddyAI with ideation stage, market research, early customer adoption and successfully achieved the product market fit. He has successfully closed funding & acquisition deal with Roadzen in 2019 and since then deeply involved in product development and launched it within 10 months of time. Nisarg has been the driving force for drivebuddyAI and he is scaling up the product & company to the next level.
Nisarg is an Electronics Engineer by education and has previously worked in Embedded domain companies like Group10 Technologies, SLS Corp & Dattus where he was responsible for developing products in the domain of IOT & Connected Vehicles. Nisarg holds Masters degree in VLSI & Embedded Systems having expertise in Embedded Software, Embedded Hardware, Cloud Services & Artificial Intelligence.
Nisarg has been an entrepreneur and driving the growth of drivebuddyAI since the inception. He is an engineer entrepreneur and started the product building at drivebuddyAI with ideation stage, market research, early customer adoption and successfully achieved the product market fit. He has successfully closed funding & acquisition deal with Roadzen in 2019 and since then deeply involved in product development and launched it within 10 months of time. Nisarg has been the driving force for drivebuddyAI and he is scaling up the product & company to the next level.
Nisarg is an Electronics Engineer by education and has previously worked in Embedded domain companies like Group10 Technologies, SLS Corp & Dattus where he was responsible for developing products in the domain of IOT & Connected Vehicles. Nisarg holds Masters degree in VLSI & Embedded Systems having expertise in Embedded Software, Embedded Hardware, Cloud Services & Artificial Intelligence.
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Notes from eChai's DeepTech Startups Meetup at Ahmedabad University
How drivebuddyAi started and what drivebuddyAI does?
DBAI is an Automotive AI startup working in the domain of Automotive Aftermarket in the category of ADAS.
What is AI in drivebuddyAI and what are the challenges about Human AI Interactions?
The drivers are usually in touch with our driver trainer team who talks to drivers and comforts them for their better safety and behavioral issues identified by the technology.
How do drivers react to AI alerts and how the resistance is being handled?
The drivers take 10-12 months of efforts to get confidence and comfort with the AI alerts i.e. a typical human psychological phase of accepting a tech in daily work life.
What are the challenges of getting a customer, investors?
DBAI is funded and was raised before Covid in 2020 and since then have progressed towards becoming one of the major players in Indian market.
What are the challenges about hiring talent, building AI models and how it was handled in the case of drivebuddyAI?
Ahmedabad specifically lacks in talent pool required for AI, dbAI has talent pool available in Delhi, Vizag, Pune, Jaipur and all these are mid experience to entry level engineers working under the managent of domain expert AI engineers to solve daily AI challenges.
Typical challenges of building AI involves data collection, data curation, annotations, training, GPUs, model optimization etc.
The DBAI journey started at a very early stage by using the pre-trained models for perception module to collecting and annotating data for Indian ecosystem when there was no Indian dataset available for building AI on it. The process of annotations, having GPUs for training purpose and managing a complete cycle of the data generation to updating a model with continuious learning is the journey in building AI.
To build AI/deep tech product startups, first one needs to start with whatever is readily available in the market which can give functional accuracy and then building on top of it by the feedback from the users, customers can help building the product focused on a specific domain.
How drivebuddyAi started and what drivebuddyAI does?
DBAI is an Automotive AI startup working in the domain of Automotive Aftermarket in the category of ADAS.
What is AI in drivebuddyAI and what are the challenges about Human AI Interactions?
The drivers are usually in touch with our driver trainer team who talks to drivers and comforts them for their better safety and behavioral issues identified by the technology.
How do drivers react to AI alerts and how the resistance is being handled?
The drivers take 10-12 months of efforts to get confidence and comfort with the AI alerts i.e. a typical human psychological phase of accepting a tech in daily work life.
What are the challenges of getting a customer, investors?
DBAI is funded and was raised before Covid in 2020 and since then have progressed towards becoming one of the major players in Indian market.
What are the challenges about hiring talent, building AI models and how it was handled in the case of drivebuddyAI?
Ahmedabad specifically lacks in talent pool required for AI, dbAI has talent pool available in Delhi, Vizag, Pune, Jaipur and all these are mid experience to entry level engineers working under the managent of domain expert AI engineers to solve daily AI challenges.
Typical challenges of building AI involves data collection, data curation, annotations, training, GPUs, model optimization etc.
The DBAI journey started at a very early stage by using the pre-trained models for perception module to collecting and annotating data for Indian ecosystem when there was no Indian dataset available for building AI on it. The process of annotations, having GPUs for training purpose and managing a complete cycle of the data generation to updating a model with continuious learning is the journey in building AI.
To build AI/deep tech product startups, first one needs to start with whatever is readily available in the market which can give functional accuracy and then building on top of it by the feedback from the users, customers can help building the product focused on a specific domain.
Featured speaker at previous eChai events:
Startup folks from various eChai meetups
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