The Scoop
Statt Inc., which uses AI to distill the vast amount of global public policy information available online, has secured $2.8 million in new funding, the company told Semafor exclusively.
The round, which closed Wednesday, was led by Moneta Ventures and Clutch VC.
Statt, a five-person startup that has remained under the radar since its launch in 2020, was founded by Steve Glickman, a former senior economic policy advisor in the Obama administration, and Andrew Platt, a former Maryland state representative.
Statt’s service pulls in a wide array of real-time data, including hundreds of millions of public policy and regulatory documents, as well as audio and video clips from all over the world. Once processed, that data can be parsed and analyzed by large AI models that have been fine-tuned for policy research.
The company’s chatbot, called StattChat, will quickly research any policy issue and generate a summary that might otherwise require days of work. Customers can also sort thorough analyses with source citations that go deeper into the data and take about five minutes to process.
“Even really specialized experts in this space don’t track all these information flows,” Glickman said. “Nobody reads through the white papers of 20 to 40 organizations in any of these roles, no matter how much time you have,”
Statt says it’s gaining traction in policy circles, with clients that include Microsoft, Visa, FTI Consulting and Avoq signing annual contracts ranging from $50,000 to over $200,000 per year. With its new funding, the company plans to grow its staff and ramp up sales.
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Among Statt’s data sources are the publications of 15,000 organizations, including think tanks, industry groups and professional associations.
Statt uses an algorithmic ranking system to determine which organizations are influential on given topics, which helps give the reports more validity. The data is constantly updated, giving customers the ability to see, for instance, whether specific issues are gaining or losing traction.
Glickman said Statt’s customers have used the tool to predict regulatory changes before they happen, based solely on the massive corpus of data it pulls into its system.
It can also be used by interest groups to decide what kind of legislation to pursue, based on subtle shifts in consensus that may not be easily spotted without the ability to see all the data.
Glickman said he and Platt at one point considered naming the company “Overton,” after the concept of the Overton window, which covers the range of policies acceptable to the mainstream at a certain time. “Our view is you can proactively move that Overton window much quicker if you understood a much broader set of the inputs into that decision,” he said.
Most of Statt’s customers are private sector companies or organizations, but it hopes to find more inside the US government, where the tool could help staffers better understand the landscape of think tanks and special interests that lobby state and federal lawmakers.
Reed’s view
While Statt’s fundraising round isn’t the kind of splashy, high dollar figure that makes waves in Silicon Valley, I was interested in the company because it’s a great example of the way AI is beginning to have an impact in the real world. And Statt is a kind of archetype for one kind of company built around advances in large language models.
In this case, the product is not the AI model itself. But it enables a new kind of service that wasn’t possible before.
Statt’s value, and potentially its competitive moat, is in the legwork of putting together a comprehensive, constantly updating stream of data in a way that can be ingested by foundation models.
The company uses its own machine learning algorithm to automatically sort all those sources by importance. That method is proprietary and no doubt informed by the founders’ combined experience in public policy.
If it’s successful, it could have an impact on how governments are run. We’ve seen an explosion of special interest groups, and that has made it difficult for some organizations, and even lawmakers, to get a clear picture of the policy landscape.
Arming everyone with better information should allow for smarter, faster and more democratic decisions.
Room for Disagreement
Another way of looking at policy, at least in the US, is that it is the result of political donations, rather than actual ideas.
From a 2013 article in Democracy Journal: “For corporations and Wall Street, campaign finance is only one weapon. The other is direct spending to influence policy. Indeed, for most organized interests, spending on elections is just the training season; the real games begin once elected officials start governing. David Koch put it bluntly: ‘Our main interest is not participating in campaigns…. Our main interest is in policy.’
This from a man who, combined with his brother and the political network he leads, spent more in the 2012 election cycle than the entire campaign of John McCain did in 2008. One wonders what he’d be spending if campaigns were his main interest.”