With a $1.5M seed round, Eloquent Labs mixes AI and Mechanical Turk to fix customer service. The startup’s special sauce is embracing a mix of AI, crowd workers on Amazon’s Mechanical Turk and traditional customer service representatives to improve experiences while cutting costs. This interplay between man and machine has saved companies a lot of money. But the thesis behind Eloquent Labs is that companies still spend too much money using customer service agents for tasks that machines can almost do, but just lack enough confidence to execute. Werling’s work in college centered around crowd-labor exchanges like Amazon’s Mechanical Turk. By integrating Turk with human customer service representatives and AI, Eloquent Labs is able to save even more money for enterprises. But, if I didn’t use the word “order” or “shipping” (oversimplifying), the model might be 62 percent sure “DHL timeline” means when will my package arrive, but its not enough confidence to act on. The other benefit of this approach is that these crowd-sourced workers are actually helping to train Eloquent’s machine learning models. Werling wants his company to take an Apple approach to the market and really nail the execution first because his company is breathing down the back of giants like Zendesk. eloquent_convo_2 A sampling of my hands-on interactions with Elle, basically trying to break it Elle was also designed to solve a number of human computer interaction problems that currently exist in the space.
Keenon Werling would be the first to agree that conversational AI is regularly overhyped. So instead of taking the traditional approach and gloating about a glitzy new deeper learning algorithm to pitch his new venture Eloquent Labs, Werling instead opted to differentiate by optimizing something far more low-tech, people. The startup’s special sauce is embracing a mix of AI, crowd workers on Amazon’s Mechanical Turk and traditional customer service representatives to improve experiences while cutting costs.
The company’s basic plan is to sell a conversational assistant named Elle to small businesses on Shopify that integrates directly with online shops to help customers with common problems like product tracking, managing returns, executing cancelations and answering FAQs. But things start to get interesting when crowd sourced labor is mixed into that more traditional model.
Companies like Digital Genus have promised “human + AI” for customer support for quite some time. To make experiences more seamless for the average person just looking to return a sweater, most startups in the space train their models to know when to give up. This stops conversations from spiraling out of control into computational purgatory. When an end user asks something not in the repertoire of the AI, a human customer service agent is seamlessly brought into the loop to finish the conversation.
This interplay between man and machine has saved companies a lot of money. Werling explains that retailers spend an average of $5 for every human customer service interaction, so every issue that can be handled with a machine is cost-saving.
But the thesis behind Eloquent…