A platform that speaks your language.

Our state-of-the-art Natural Language Processing understands and responds to your questions, just like a coworker.

A symphony of enterprise natural language processing.

No single algorithm is up to the task of understanding the complexities of human communication, so we developed our own machine learning ensemble.

Like a conductor interpreting the nuances of their piece, our NLP ensemble determines a user’s intent, credentials and permissions, questions they’ve previously asked, apps and systems they have access to, and the context of the larger conversation—in milliseconds—to hit the right note.

Algorithms here, algorithms there, algorithms everywhere.

The 40+ industry-standard and proprietary algorithms in our machine learning ensemble empower Capacity to interpret and answer a wide array of inquiries.

  • We get what you’re trying to say

    Our algorithms leverage spell checking, word importance, entity recognition, term frequency, acronym translation, vectorization in semantic hyperplanes—we could go on.

  • And if we don’t get it, we will

    Each time Capacity receives positive or negative user feedback, our machine learning and neural networks leverage that data to continuously
    improve the model.

How a machine listens

Our AI analyzes the context and semantic structure of every question, determining the best candidate from a weighted list of potential query matches.

Asked and answered

If the algorithm ensemble reaches a threshold of confidence in a potential match, Capacity instantly surfaces an answer to the user’s question.

What teammates are for

If not, a human-in-the-loop matches it to an existing exchange, creates a new exchange, forwards it to an expert within the org, or simply dismisses the question.

Let’s be clear

For any query that falls into the band of uncertainty, a list of options are presented to the user. Any selection or thumbs-up/down is then fed back into the ML loop.

From Natural Language Processing to Natural Language Understanding

  • 01

    How a machine listens

    Our AI analyzes the context and semantic structure of every question, determining the best candidate from a weighted list of potential query matches.

  • 02

    Asked and answered

    If the algorithm ensemble reaches a threshold of confidence in a potential match, Capacity instantly surfaces an answer to the user’s question.

  • 03

    What teammates are for

    If not, a human-in-the-loop matches it to an existing exchange, creates a new exchange, forwards it to an expert within the org, or simply dismisses the question.

  • 04

    Let’s be clear

    For any query that falls into the band of uncertainty, a list of options are presented to the user. Any selection or thumbs-up/down is then fed back into the ML loop.