What we do
We automate costly and complex online intelligence gathering activities.
FilterLabs.AI scours the world’s online communications to make sense of every local community’s needs, issues, and understandings of the world. Using NLP models tailored to these communities we provide actionable intelligence to help organizations reach the world with their message.
It has become increasingly difficult to connect with audiences, markets, and communities where they live and work. We go hyper local with our analysis and target alternative data sources so you know exactly what matters not just in your city, but in every neighborhood.
Working at the University of Virginia, Jonathan started to experiment with ways to capture granular community-level data where social media platforms were silent. While working to capture data in Pakistan, Jonathan began pioneering ingestion strategies to understand what local communities care most about. The fundamental insight was born: to understand what people care about and who they trust, organizations, governments, and campaigns needed to turn off the social media feeds and reconnect with audiences, markets, and communities where they live, work and play.
While living in Berlin, Jonathan started to conceive of ways to apply the same data ingestion and analysis strategies to help a broader set of organizations, companies, and agencies in the US understand what matters most to those they are trying to serve. He solved this problem in far-flung locations around the world — why can’t it be done at home, where the social fabric is rapidly decaying. Organizations desperately needed to reconnect with communities to begin to rebuild the trust that had been lost over the last several decades. So over the course of COVID lockdowns, Jonathan developed a prototype to capture and analyze community-level data from the smallest town in Oklahoma to the micro-neighborhoods of Brooklyn.
Seeing several broad use cases for community-level data, Jonathan, David and Ayo formed Filter Labs AI to scale these solutions globally. Our first customers had been spending money tapping into Twitter and social media platforms to find nothing new or were paying consultants and analyst firms to give their opinions. The results, however, proved unreliable, limited and narrow. Connecting with the right audience, market and community was too important for such limited understandings. Filter was built to help these organizations, companies, and agencies reconnect with what matters most in their communities and markets.
DR. JONATHAN D. TEUBNER
Chief Executive Officer
Jonathan has served in a number of leadership capacities in academia, business, and non-profits and has pioneered the application of machine learning to improving peace building methods. At the University of Virginia, Jonathan led a collaborative team of data scientists and scholars across the social sciences to create NLP tools. Previously, Teubner was Co- Director of Global Covenant Partners and Economist at Lehrman, Bell, Mueller and Canon in Washington, DC. Since 2021, Jonathan has been Visiting Faculty at the Human Flourishing Program at Harvard University, where he leads the Social Connectedness Research group. Teubner has a Masters degree from Yale, a PhD from Cambridge, and has held fellowships at the Sorbonne in Paris, the Humboldt-Universität zu Berlin, and Yale.
David P. Smith
Chief Technology Officer
David most recently served as Director of Engineering at A Cloud Guru. Previously, he was VP of Technology at Linux Academy. David has gained extensive experience in full stack development, agile methods, dev-ops, management of security and engineering processes, and team leadership in a wide range of tech startup scenarios. His experience ranges from Cloud based application development, database management, security administration, to Natural Language Processing corpus collection and training. In his academic career he specialized in language and literary theory. David has Masters degrees from Princeton Seminary and Yale.