A sign of the times…an AI startup has announced a generative AI platform aimed at automating workflows for customer support agents.
Artificial intelligence startup Yellow.ai recently announced the release of a generative AI platform, named YellowG, which is aimed at automating workflows for enterprise customers.
Formerly known as Yellow Messenger, the startup’s most popular product is an omnichannel chatbot, which was integrated by NGOs and hospitals in 2021 during the Covid-19 pandemic, as a first point-of-contact for patients providing details of their symptoms. From there, it was able to arrange appointments, and give advice.
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This is an expansion on the chatbot, which can be integrated into various workflows which involve customer to business communication. It leverages the capabilities of enterprise GPT, alongside Yellow.ai’s own generative solution, and has been optimized to provide near-human empathy, and the ability to change the conversation flow to match the customer.
“Our new platform is the first to achieve zero setup time, guaranteeing instant usage from when a bot is built,” said Yellow.ai CEO and co-founder, Raghu Ravinutala, to VentureBeat. “With its robust, enterprise-level security, it ensures maximum safety through a blend of centralized global and proprietary large language models (LLMs). Our productization of real-time generative AI is designed specifically to propel enterprise conversations. This means YellowG can generate workflows dynamically while easily handling complex scenarios.”
One of the major drawbacks of deploying generative AI systems into enterprise-level operations is the likelihood that the chatbot will experience hallucinations, which occurs when there is a gap in the AI’s knowledge which it fills with false information. Yellow.ai said that its chatbot maintains an impressive “near zero” hallucination rate, and a response intent accuracy rate of 97 percent.
There are huge upsides to deploying this technology early however, especially for enterprises which are overwhelmed by the volume of customer conversations. Instead of having a bot that can only interpret a few sentences, and can only direct to FAQ or support pages, generative AI can play a much more active role in sorting out customer enquires, reducing the load for human support agents.
“By leveraging reinforcement learning, businesses can optimize these variants to improve conversion rates,” said Ravinutala. “This approach enables the creation of dynamic content for a comprehensive experience with enterprise-grade dynamic AI agents. Some prominent enterprise use-cases where generative AI can enhance the capabilities of conversational systems include customer support, conversation flows, and goal-based conversational marketing.”
Yellow.ai have worked on conversational AI services for years now, and connecting it with generative AI systems could be the final piece of the puzzle for providing an end-to-end virtual customer support experience. Other workflows outside of customer support can also utilize this technology, although Yellow.ai appears to be prominently pushing their experience with customer support chatbots.
“Beyond creating chatbots, we are focusing on utilizing LLMs as a robust intelligence layer to provide solutions for complex end-user-facing use cases that require real-time decision-making,” said Ravinutala. “Our generative AI-powered features like goal-oriented conversations have gained significant interest and rapid adoption. Additionally, we also recognize the importance of responsible and ethical AI practices.”
Customer support is one of the few areas where we could see near complete removal of the human workforce over the next decade, if generative AI tools are as sophisticated as their creators would have us believe. Vodafone said it would reduce its workforce by 11,000 in the next three years, with customer services expected to be hit heavily and possibly replaced with AI. British internet provider BT announced similar reductions, with its CEO estimating 10,000 job cuts by 2030 due to AI.
