Prateek Srivastava,Co-Founder& CEO
Shobhit Agarwal, Co-Founder & CTO
What the world knows about Artificial Intelligence(AI) is still less if compared to what’s going to happen on it over future course of time. Considering the market structure in India, two of the native souls decided to create something that adds value to the growing acceptance of AI related technologies in the country. “Both my Co-Founder Shobit and I were working professionals in the US and we headed back to India to start something on our own and we founded a company called Adoro which was a social fashion marketplace curated by AI. We ran it for about 2 years after which we realised that there is a bigger problem in terms of new comers as well as other online consumer companies and there is a common need for a platform to solve AI problems for these companies. There is a big technological gap and, while there is a lot of focus on the AI technology but there is a large gap in terms of knowledge, in terms of skillset in the people”, says Prateek Srivastava, Co-Founder & CEO, Couture.ai.
The Experience that Matters
Both Prateek and Shobit have undergone considerable experience in this sector before they thought of creating something on their own. Couture.ai was born out of the knowledge that was gained by the founders during their work in multiple organisations across the world. It took them almost two years after homecoming to come up with something that will help develop the potential of AI for any given enterprise, big or small. “Couture.ai helps you deploy enterprise-wide artificial intelligence. We have a great history of helping customer products scale efficiently and provide best in class returns on investment. Through this platform a company can use AI to its own advantage without investing huge amount of time in gathering data, training models and implementing full stack solutions”, says Shobhit Agarwal, CTO & Co-Founder.
" Through couture’s platform, a company can use AI to its own advantage without investing huge amount of time in gathering data, training models and implementing full stack solutions"
Industry Applicable For
Witnessing the gradual developments in the field of AI and Machine Learning (ML), the applications of the same seems to be diversifying. That is the primary reason maybe as to why innovative technology companies such as couture.ai are being provided support by external factors. “We started with
Both Prateek and Shobit have undergone considerable experience in this sector before they thought of creating something on their own. Couture.ai was born out of the knowledge that was gained by the founders during their work in multiple organisations across the world. It took them almost two years after homecoming to come up with something that will help develop the potential of AI for any given enterprise, big or small. “Couture.ai helps you deploy enterprise-wide artificial intelligence. We have a great history of helping customer products scale efficiently and provide best in class returns on investment. Through this platform a company can use AI to its own advantage without investing huge amount of time in gathering data, training models and implementing full stack solutions”, says Shobhit Agarwal, CTO & Co-Founder.
" Through couture’s platform, a company can use AI to its own advantage without investing huge amount of time in gathering data, training models and implementing full stack solutions"
Industry Applicable For
Witnessing the gradual developments in the field of AI and Machine Learning (ML), the applications of the same seems to be diversifying. That is the primary reason maybe as to why innovative technology companies such as couture.ai are being provided support by external factors. “We started with
mostly retail. We have worked in travel as well as hospitality. So,we have couple of clients in travel and hospitality. We had our initial clients in Germany in ticketing space, similar to MakeMyTrip, but for EU and now we are looking at verticals like media, healthcare and finance. We started in 2017. We got accelerated by a Paris-based accelerator called Numa. So, at the end of acceleration we did the incorporation which happened in 2018”, says Prateek.
Impact on the Market
The couture.ai platform is designed in such a way that even the largest global enterprises can implement vertical products on top of couture’s proprietary ML and deep learning innovations. Expressing the goodwill of the company, the founders conclude,“We basically work with large scale enterprises that already have existing systems in production. They are already having consumer base and consumer apps where consumers are interacting with their products. Our platform goes and sits behind their system. We collect all the data that consumers are generating. A lot of behavioural data is unstructured. We take all that unstructured data and aggregate and transform it into more structured format which can be used for machine learning or deep learning which are collectively called AI models. The AI system basically then gives you output such as prediction about the users or things like customer segmentation or product segmentation which have multiple use cases in different verticals.”
Impact on the Market
The couture.ai platform is designed in such a way that even the largest global enterprises can implement vertical products on top of couture’s proprietary ML and deep learning innovations. Expressing the goodwill of the company, the founders conclude,“We basically work with large scale enterprises that already have existing systems in production. They are already having consumer base and consumer apps where consumers are interacting with their products. Our platform goes and sits behind their system. We collect all the data that consumers are generating. A lot of behavioural data is unstructured. We take all that unstructured data and aggregate and transform it into more structured format which can be used for machine learning or deep learning which are collectively called AI models. The AI system basically then gives you output such as prediction about the users or things like customer segmentation or product segmentation which have multiple use cases in different verticals.”
