Yellow.AI, an artificial intelligence-first customer service automation firm, has partnered with at least four Indian IT services companies including Tata Consultancy Services (TCS), Infosys, HCLTech, and Tech Mahindra. These partnerships are focused on leveraging Yellow.AI's platform for HR automation and customer service automation solutions.
“So from a partnership standpoint, we've been working with a lot of global system integrators to go and sell to large enterprises, large businesses across the globe,” Rashid Khan, co-founder and Chief Product Officer, of Yellow.AI, told Moneycontrol, without disclosing when these deals were signed.
The partnerships assume significance as IT companies have been increasingly tying up with firms to provide generative AI (Gen AI) services to both external clients and internal employees.
These collaborations aim to utilize Yellow.AI's advanced platform to enhance human resource (HR) automation as well as customer service capabilities across various sectors globally.
“For anything related to AI, they want to start using the Yellow platform, especially when they look at scenarios for customer service employee automation,” Khan said.
The company was founded in 2016 by Raghu Ravinutala, Jaya Kishore Reddy Gollareddy, and Khan, and offers AI-first customer service automation to enterprises. Yellow.ai has successfully deployed over 150 generative AI bots for enterprises with over 1,100 enterprise customers, including Hyundai, Volkswagen, ITC Ltd, and Asian Paints.
The firm has raised more than $100 million in funding and counts Lightspeed, WestBridge Capital, Sapphire Ventures, and Salesforce Ventures as its investors.
Global and Regional SIs
In regions where global system integrators (SIs) such as TCS and Infosys have a limited presence, Yellow.AI collaborates with regional SIs to offer local market requirements. “When you go to a lot of APAC (Asia-Pacific) countries, a lot of the global SIs are not very active in that region. So Indonesia, Thailand, Philippines, etc. The very regional companies are sort of active there. So we work with a lot of regional,” Khan explained.
Some of these regional SIs are Quadrafort for India and other markets, EGuardian for Sri Lanka, Soltius for Indonesia, and Masterconcept for APAC.
“It's just that the access that regional SIs have in certain regions is a lot more than what a global SI would have,” Khan said. He added that regional SIs are also able to amplify customer experience Gen AI by having a very targeted user list.
For example, in the insurance vertical, Yellow.AI works with customers for a complete end-to-end process from policy buying to answering questions on policy to what is included/excluded from the policy.
Additionally, Yellow.AI works with local boutique firms too. “For boutique firms, a lot of focus is on customer experience use cases. So there are firms who just largely help businesses formulate their strategy on how their customer communication should look like.”
These boutique firms assist businesses in developing and implementing comprehensive customer service strategies using Yellow.AI’s platform.
“With boutique firms, the idea is largely on customer experience use cases. So how can they recommend a product that can look like a full stack of customer service,” Khan said.
Leveraging AI/ML
Yellow.AI’s platform is built on AI and machine learning technologies, primarily hosted on Amazon Web Services (AWS). Khan says the company’s computing is predominantly on AWS, using the latest products like SageMaker and Bedrock, which are predominantly ML workflow and model hosting services.”
AWS’ Bedrock is used to build and scale Gen AI applications with foundation models, whereas SageMaker is a managed machine learning service in general.
Furthermore, Yellow.AI is working on projects like the Komodo 7P model, a large language model trained on 8.3 billion tokens. “We're trying to get that on Bedrock right now, which can be used by other companies as well,” Khan said.
Last month, the company said that it plans to launch large language models (LLMs) in Kannada, Hindi, and Tamil among others, specifically for customer-service functions, amid rising demand for Indic language models.
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