Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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Rulai launches low-code chatbot development tool and raises $6.5 million

By Nand Kishor |Email | May 26, 2017 | 5445 Views

Customer experience chatbot developer Rulai has launched a new "low-code" chatbot development tool and raised $6.5 million to roll it out.

The development team at Rulai, with offices in Beijing and Campbell, Calif., is helmed by the renowned University of California, Santa Cruz, computer science professor Yi Zhang.

Professor Zhang, the company's chief technologist, and her team are launching a product that customer service managers can use to develop chatbots that will perform tasks based on customer conversations, and that can be created without a single line of code.

It's an example of how software developers and artificial intelligence systems are writing themselves out of the application development process.

Specifically, the Rulai tool was designed for customer service managers. Using Rulai's drop-down toolkit, managers can write scripts and create action items to customize chatbots that will perform functions based on their communications with customers.

In the demo I saw, Professor Zhang created a chatbot that could automatically respond to a customer and cancel and rebook their flights through a series of drop-down menus and an integration with a company's back end.

The chatbots rely on natural language processing technology developed by Rulai, and the customization toolkit the company has built will let managers with no coding experience create their own scripts. Based on user's responses, the bots will respond with actions that are also created by the managers.

Rulai is throwing its bot toolkit out into an incredibly crowded market. Everyone from big names like Facebook and Microsoft to startups like BotCube, Azumo, Api.ai, Chatfuel, blahblahbot, pandorabot and RoBotOverlord (I made the last three up, but you get the idea) are working on these things.

For Rulai, another point of differentiation it's pitching is the strength of its AI technology itself, according to Zhang.

The company's bot can escalate tasks to a human customer support system when needed; perform several rounds of communication with a customer and remember the context of the conversation; it's based on mixed initiatives and mixed tasks technology, which means both the bot and the human can lead a chat; and it adaptively changes its approach based on real-time feedback.

Whether or not the company's chatbot development toolkit is the future, Rulai has lined up some serious backers to finance its growth.

To roll out this new product, Rulai has raised $6.5 million in new financing from a slew of Sino-U.S. investment firms led by GSR Ventures, a huge player in the Chinese venture capital industry, and an established presence in the U.S.

With over $1.5 billion under management in U.S. and Yuan-denominated funds, GSR has backed some of China's biggest new startups. Companies in the fund's portfolio include DiDi Chuxing, Qunar, ele.me, Xiaohongshu, Inke, Shanghai DZH and ofo.

Additional investors in the round included the former venture arm of FIL, formerly known as Fidelity Growth Partners and now called Eight Roads Ventures China and Zhongwei Capital. Read More


Source: TC