• Orchestrator LLM addresses the problem of broken customer conversations through accurate query identification, retention of conversation history, and seamless context switching across channels, boosting customer satisfaction by 60%

• It understands the customer intent and triggers the appropriate tool without manual training, thus cutting down on operational costs by 60%

Yellow.ai, a global leader in generative AI-powered customer service automation, launched Orchestrator LLM, an industry-first agent model that determines the most suitable next step while engaging in personalized, contextually aware conversations. By retaining context, the generative AI agent model enables faster and accurate issue resolutions, resulting in more than 60% increase in customer satisfaction.

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Traditional chatbots often suffer from a lack of contextual awareness and memory of past interactions, which can lead to disjointed conversations and customer dissatisfaction. These limitations stem from their restricted ability to handle queries beyond programmed responses, due to insufficient training on intents and utterances. However, with the emergence of Large Language Models (LLMs), enhancing personalization in automated customer experiences has become increasingly attainable. Leading this innovation, Yellow.ai’s Orchestrator LLM directly tackles these challenges by:

• Enhanced Customer Experience with Advanced Context Switching: Orchestrator LLM excels in context switching and engages in small talk, ensuring smooth transitions between queries for an uninterrupted user experience. It skillfully analyzes conversations, recognizes multiple intents, and maintains context, guiding users toward their primary goals while minimizing abrupt endings. By retaining past interactions within a memory window and revisiting original queries, Orchestrator LLM facilitates more comprehensive, human-like conversations.
• Zero Training for Maximum Operational Efficiency: Orchestrator LLM provides the best solutions tailored to customer needs without requiring any prior training. It makes real-time decisions about activating the appropriate agentic workflow or conversational flow in response to user requests. For example, the model can instantly determine whether to retrieve information from a knowledge base, initiate a new conversational flow, or escalate to a live agent, all while retaining the context of the conversation. This streamlining of processes significantly cuts operational costs by 60% and boosts agent productivity by 50%.

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“Unlocking the full potential of LLMs requires a strong orchestration framework. Our Orchestrator LLM serves as a central integration hub, seamlessly collaborating with various AI tools and backend systems to deliver more cohesive and personalized customer experiences,” said Raghu Ravinutala, CEO & Co-founder, Yellow.ai. “The launch further underscores our commitment to developing multiple in-house LLMs and driving our mission to redefine the customer service sector through AI-first solutions that deliver human-like experiences autonomously.”

“Orchestrator LLM can truly revolutionize the customer service industry. Its ability to anticipate customer needs and deliver instant, relevant responses will boost customer loyalty and operational efficiency,” said Eric Hansen, CIO, Waste Connections.

The company is making significant strides in developing multiple in-house LLMs for diverse customer service use cases. It launched the YellowG LLM for zero setup, goal-oriented conversations, summarization, and Q&A answering, along with Komodo-7B, Indonesia’s first model for customer support in 11+ regional languages. With a less than 1% hallucination rate and an average response time of 0.6 seconds, these LLMs are designed to meet the rigorous standards set by enterprises, ensuring secure, precise, and personalized customer interactions. Moreover, the company has successfully deployed 150+ generative AI bots for enterprises, showcasing its robust generative AI capabilities and focusing on delivering AI-first solutions for customer service.