Declara raises $16M to apply machine learning personal learning

Declara, a Palo Alto, Calif., startup that  aims to help individuals in large professional networks learn new information, has raised a $16 million series A round of venture capital. GSV Capital led the round, with participation from Data Collective, Founders Fund and Catamount Ventures.
Declara’s product is like a social network platform, often connecting large national organizations, and like any good social network it uses a variety of machine learning techniques to cater recommendations to individual users. However, because it’s focused on education, Declara connects members to other members, outside experts and content related to the areas they’re trying to learn. Rather than relying solely on users’ stated interests, the platform studies their online behaviors and makes suggestions accordingly.
Here’s how Declara Founder and CEO Ramona Pierson (pictured above) — who has a triumphant personal story, too — described the company on the Structure Show podcast in March:

“We really try to personalize around preferences and validate those preferences. So, if someone says I’d rather learn through video or rich media, but yet we actually start to validate the system going, ‘Oh, they actually do best when they’re trying to help others. When they’re an expert in helping others, they’re actually learning faster.’ So we’ll take in the preferences and things that people declare about themselves — thus [calling the company] Declara — but then we also validate with our programs.”

You can listen to the whole interview below.
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Pierson also spoke at our Structure Data conference, where she discussed her experience recovering from a horrific accident and how that inspired her future work in trying to help adults learn — a career arc in which Declara is just the latest endeavor.
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