Yellow AI launches dynamic automation platform powered by generative AI for enterprises

Yellow AI launches dynamic automation platform powered by generative AI for enterprises
Written by Techbot

San Mateo-based Yellow AI today announced the launch of its Dynamic Automation Platform (DAP), powered by generative AI. According to Raghu Ravinutala, CEO and cofounder of Yellow AI, the DAP is built on a multi-LLM architecture that is continuously trained on billions of conversations to ensure scalability, speed and accuracy. The platform’s generative AI powers its ability to automate customer and employee experiences across channels, significantly reducing operational costs. Ravinutala claims that businesses using DAP can achieve 90% automation within the first 30 days, a 40% increase in CSAT ratings, and save up to 60% in operational costs. 

Yellow AI’s rebranding and the launch of its DAP mark a significant milestone in the company’s growth journey. With a 4 times growth rate in North America and an established presence in the Asia-Pacific and Middle East markets, Yellow is committed to using technology, mostly generative AI, to enhance its existing offerings such as the Conversational Service Cloud, Conversational Commerce Cloud and Conversational EX Cloud product suites. 

Most recently, the company launched the Dynamic Conversation Designer — a chatbot conversation design tool that utilizes generative AI to help teams design conversations quickly and easily without any coding. Integrated within the Yellow conversational AI platform, the tool automatically creates development flows from design flows, eliminating the need for developers to start from scratch and saving significant development time and effort. The tool also ensures instant autosync between design and development flows, resulting in a claimed 50% faster time to market with reduced development and training time.

The DAP is multicloud and multiregion, built to meet the highest security standards and compliance requirements. It integrates with existing systems and workflows and can create personalized and context-aware conversations with customers. With 100+ integrations and 150+ prebuilt marketplace templates, Yellow AI claims that businesses can go-live and to market 2 times faster. The platform offers three solutions: Conversational Service Cloud, Conversational Commerce Cloud, and Conversational EX Cloud.


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Yellow’s Conversational Service Cloud (CSC) solution enables enterprises to deliver real-time support to their customers by automating routine queries and transferring complex queries to human agents. Enterprises can expect to deliver a 24×7 instant, omnichannel customer support experience with up to 60% reduced operational cost and faster ROI. CSC claims to deliver key benefits such as a 40% increase in CSAT, 60% reduction in operational costs, 90% automation within 30 days, and 50% increase in human agent productivity.

Yellow’s Conversational Commerce Cloud (CCC) solution connects consumers to the brand directly via personalized, relevant omnichannel conversations and increases conversions across the entire customer life cycle. The platform enables marketers to reach and engage with users across channels, driving a boost in conversions across the funnel. CCC promises to deliver a 60% increase in customer engagement, 30% decrease in cost per lead, and 50% increase in conversions.

Finally, Yellow’s Conversational EX Cloud delivers on-demand, personalized employee experiences at scale. With EX Cloud, employees get round-the-clock support with self-serve automation to address all day-to-day queries. As per Yellow AI, businesses using the EX Cloud can expect an 80% employee queries self-served, 40% increase in ESAT, cut operational costs up to 60%, and 30% faster hiring and onboarding.

Powering DAP with generative AI

In an exclusive interview with VentureBeat, Ravinutala explained that Yellow AI has combined generative AI technology with their proprietary AI engine, which holds all the data, behavior and experiences collected by their Dynamic AI agents to deliver business outcomes.

Ravinutala highlighted that traditional rule-based automation chatbots face limitations in complex problem-solving, emotional intelligence and empathy, adaptability and learning, and communication barriers. When confronted with complex issues, these chatbots rely on predefined, guided flows, which restrict their flexibility and require human intervention in decision-making. However, advanced AI models can enhance problem-solving capabilities by dynamically adjusting their responses to deliver more accurate and efficient solutions at machine speed.

Emotional intelligence and empathy are essential for addressing sensitive customer interactions, which chatbots, even with state-of-the-art AI, struggle to fully emulate. By leveraging generative AI, chatbots can now produce more human-like conversations, modulate their tone and personalize responses for each individual. This advancement enables empathetic and accurate communication, as demonstrated in scenarios such as flight cancellations, resulting in a tailored service experience at machine speed powered by the CDP.

AI chatbots can learn and improve over time, but they may not be as adaptable as human agents who can rapidly respond to unique or unforeseen situations. Further research and development in AI algorithms can help bridge this gap, enhancing chatbot adaptability and capacity for continuous learning, which will ultimately benefit user experiences.

Misunderstandings and communication barriers are common challenges for chatbots, as they can occasionally misinterpret user queries or context, leading to incorrect or irrelevant responses. Advancements in natural language processing (NLP) and understanding (NLU) can help overcome these limitations, enabling chatbots to grasp context and user intent more accurately. This will ultimately lead to more effective communication and improved user satisfaction.

Generative AI also removes two key limitations of traditional rule-based automation. Firstly, advanced intent training eliminates the need for businesses to spend time and resources training intents at the bot level. Secondly, dynamic rule-based flows enable AI-powered chatbots to cater to a broader set of user requests with minimal setup effort, ensuring that customers receive accurate and relevant responses to their inquiries. 

“Combining DAP with generative AI capabilities marks the next step in our mission to transform the way businesses interact with their customers. Our advanced generative AI technology enables dynamic, goal-oriented, and human-like conversations, ensuring customers receive an unparalleled support experience,” said Ravinutala. 

The platform offers continuously learning multi-LLM models for all industries, near-human experience at machine speed and a long list of features powered by generative AI technology. 

One of these features is the Dynamic Chat, which enables goal-driven conversations and generates conversation flows on the fly. Enterprises can set lead generation goals and configure mandatory and optional inputs, and Dynamic Chat generates leads in real time and stores them in the CRM. This feature helps improve customer journey completion rates by 50% and requires zero setup, resulting in faster time-to-market.

Yellow’s Inbox is another feature powered by generative AI technology, providing customer support help desk for omnichannel support. Inbox empowers support agents with AI-enabled ticket summarizations, response and tone suggestions, and multilingual agent interface capabilities. These features help agents handle customer queries faster and reduce search and training time, leading to a 50% increase in agent productivity and reduced search and training time by 50% and 80%, respectively.

Dynamic Workflow Generator enables the auto-generation of workflows for both marketing and customer support use cases, helping marketers define more nuanced goals and resolve customer issues without relying on if-else loops. This feature also triggers automatically generated workflows based on customer inputs, achieving 90% automation within 30 days.

“Traditionally, enterprises use chatbots to provide responses to a fixed set of flows. The enterprise tries to predict the probable journeys that the customer may take or the questions they may ask during each of those journeys and accordingly the chatbots are trained to provide responses to the questions. This approach comes with an inherent limitation of being static and expecting customer situations to stay within those predicted journeys. But real-life customer scenarios are very dynamic and the market need is to have Dynamic AI agents across chat and voice that can generate responses on runtime to changing customer situations,” said Ravinutala.

The Dynamic Workflow Generator enables auto-generation of workflows for marketing and customer support use cases revolutionizing campaign strategies and issue resolution. Marketers can now craft goal-focused dynamic campaigns, like promoting special discounts, driving successful conversions. Similarly, customer support benefits from the dynamic creation of workflows, eliminating the reliance on if-else loops and accelerating query resolution with greater scope and efficiency.

AI Content Engine for Marketers delivers increased efficiency and results through generative AI-powered messaging templates, enabling the auto-generation of contextual templates based on campaign goals and user segments. The Template Tone Configurator feature helps align templates with the brand’s image, resulting in a 60% improvement in user engagement and 2 times faster go-live with autogenerated templates.

SearchGPT automates queries in minutes with zero setup, allowing for rapid deployment of Dynamic AI agents using Yellow AI’s DynamicNLP and OpenAI API (GPT-3) models. This feature enables increased call deflection and provides tangible business value for enterprises, achieving a 60% call deflection rate.

Webconvert is a feature that analyzes page content with dynamic AI bots to understand user interests and increase conversions by 50%, while also reducing cart abandonment rates by 30%.

Lastly, Conversational Insights provides 20+ real-time actionable insights to help make informed decisions based on key performance indicators such as deflection rate, goal completion rate (GCR), customer satisfaction (CSAT), first response time (FRT) and more. The Dynamic Automation Platform also offers an extensive layer of security, access control and approval mechanism, ensuring SOC 2, HIPAA, ISO, and GDPR compliance and eliminating the risk of generative AI hallucinations.

The road to complete conversational workflow automation

Yellow AI’s recent rebranding is a clear indication of the company’s commitment to its vision of delivering human-like conversational experiences powered by generative AI. This move is a critical milestone for the organization and highlights its unwavering commitment to its generative AI roadmap to stay ahead of the curve in providing innovative solutions that empower businesses. The rebranding is captured by the new tagline, “Memorable Conversations, Everytime,” which reflects the company’s unique position in providing exceptional, engaging, and autonomous experiences for both customers and employees using AI-driven conversations.

“Generative AI has opened up new avenues for us as a company, and we are excited about the increasing interest from enterprises in adopting our Conversational AI solutions. We strongly believe in the potential of generative AI to enhance our capabilities, foster innovation and drive business growth,” said Ravinutala. “For almost two years, we have been working with LLMs and continue to invest heavily in domain-specific LLMs to facilitate dynamic content creation. We are already working with enterprises across sectors such as BFSI and automobile sectors to leverage our generative AI-powered capabilities for their customer support and marketing use cases. In fact, generative AI and LLMs have become ubiquitous in almost every customer conversation,” he added. 

Yellow is doubling down on its generative AI roadmap to bring its solutions to more enterprises with faster time-to-market and time-to-value. The company aims to leverage LLMs as a robust intelligence layer, not just to create chatbots, but to deliver solutions for complex end user–facing use cases that require real-time decision-making. Its focus is to enhance end user–facing features like goal-oriented conversations, making it easier to define and execute a more extensive and complex range of goals. Additionally, Yellow is investing in widening the scope of its Dynamic AI agents using dynamic workflow generation and delivering individualized service through a combination of CDP and LLMs. It is also experimenting with different LLMs like Anthropic and Meta’s LLaMA, while also building an in-house LLM specifically designed for enterprise consumption to further strengthen its platform capabilities.

To make bot-building more accessible and straightforward, Yellow is committed to introducing a new feature that allows users to describe the kind of Dynamic AI agent they need, and its platform will automatically build it for them. This feature will be available to all users of the platform, making it incredibly easy to unlock all the benefits of the technology. Yellow is continuously working to differentiate itself and stay at the forefront of conversational workflow automation.

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