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An industry-wide shift to greater use of conversational AI, often in the form of chatbots and voice assistants, is clearly underway. However, the success of these interactions depends on the quality of conversation design, a new domain for most developers and one that may hinge on subpar or outdated tooling. This is the challenge San Mateo, CA-based seeks to address with its conversational AI platform. suggests that problems in this burgeoning area often reside in the design process itself. Though design is a crucial step in developing conversational AI, the process is often hindered by the use of flowchart-based tools that result in clunky and complicated designs. This not only slows development, it creates a disjointed experience for users, who encounter inconsistent design choices and interactions across different conversational interfaces.

One of the key pain points in conversation design is in the basic approach. Most designers are relying on flowchart-based tools that are not optimized for designing conversations. This makes the design process time-consuming and cumbersome, leading to subpar outcomes. As well, replicating design flows in development is a tedious and inefficient process.

With the launch of its Dynamic Conversation Designer, Yellow.AI looks to improve the design process for chat and voice conversational workflows using generative AI. Integrated within the conversational AI platform, this conversation design tool allows teams to design chatbot conversations without writing any code, saving significant development time and effort. 


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The Dynamic Conversation Designer creates development flows automatically from design flows, eliminating the need for developers to start from scratch. Moreover, there is instant auto-sync between design and development flows. With this, the company claims to deliver a 50% faster time to market, along with reduced development and training time. goes with the flow’s CEO and cofounder, Raghu Ravinutala, told VentureBeat that the company’s Dynamic AI Collaborator add-on will democratize the use of generative AI technology. With it, he indicated, the Dynamic Conversation Designer can provide suggestions to designers by sharing the next probable flow and alerting them to errors. This is enabled by generative AI. The software also boasts a tighter integration with the Marketplace.

The company’s platform competes in an increasingly active field. A recent market insight report by SkyQuest predicts a compound annual growth rate (CAGR) of 28.3% for the conversational AI market from 2022 to 2028. This growth is expected to catapult the market value from USD $9.6 billion in 2021 to $46.4 billion by 2028, indicating that businesses recognize the value of this technology. sees customers wanting to integrate their bots with their systems to take actions on behalf of end users, not just build a FAQ bot. Within a Conversation Studio, bot flows are auto-synced, and API integrations are added as necessary.

The road ahead for conversational AI

Since its inception in 2016, has striven to automate customer and employee experiences using the best of AI and human intelligence. In 2022, the company introduced several new products and updates, including pre-built dynamic AI agents, a customer data platform (CDP) called Engage, and feature enhancements to its voice AI automation solutions. 

These updates are meant to make the conversational experience more human-like and faster, with a 50% improvement in response times to customer queries. Additionally, the company has produced an Employee Experience suite and proprietary DynamicNLP technology that uses zero-shot learning to enable quick deployment and intent accuracy of over 97%. is focusing on improving its dynamic AI agents to create more emotional and human-like interactions. With phone calls remaining the primary mode of customer support, the company has made significant improvements to its voice AI product, resulting in a claimed two-fold increase in accuracy and reliability. The company plans to continue investing in its voice offerings, with the upcoming launch of its 2.0 version.

Ravinutala said that is investing heavily in domain-specific large language models (LLMs) to enable dynamic content creation for a comprehensive experience with enterprise chatbots and virtual assistants. The company plans to use generative AI to allow anyone to train custom intents specific to their business. 

“Currently, workflow creation and integration in conversational systems are manual and rigid, even if they are created with integrated no-code tools. This is an area of generative AI that is still unexplored, and the roadmap is working towards enabling the dynamic creation of workflows embedded within conversations,” Ravinutala said.

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