Chatbots & Conversation Agents

Conversations are impossible without training data at scale

Don’t release a conversational agent that nobody wants to talk to.

We train both audio and text assistants. Here’s how:

Relevance, Intent, and Utterance Collection

Text-based agents and chatbots need copious training data to be successful. At Figure Eight, we can grade relevance and intent and collect short utterances or match phrases that look different but, to a bot, mean essentially the same thing.

Entity Extraction

Entity extraction–or named entity recognition–is an important step in training any natural language processing algorithm. For chatbots and text agents, having in-domain examples for the concepts and ideas you care most about is paramount.

Audio & Speech Recognition

We handle more than just text. Our flexible platform can train, test, and tune voice recognition algorithms. We have humans-in-the-loop fluent in dozens of languages too, so no matter who you’re trying to understand, we can help.

Trusted by today’s leading brands

When we changed to Figure Eight, within a few weeks, we saw that labeler accuracy go up to 88% and it stayed in the high 80s and 90s for us ever since, even across a large diversity of models. That’s been a really, really big win.

Etienne Manderscheid

VP Engineering, AI - Machine Learning

View Case Study »
Learn how Home Depot uses machine learning and high quality data to make every customer experience, no matter how they’re shopping, a whole lot better.
Walking through the field, taking tallies on how many weeds we hit, how many we missed, and our accuracy was in the high 90s on that test. We’re really excited about bringing this technology to the farmer and using AI to really modernize farming.

Chris Padwick

Machine Learning Team Lead

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