When OpenAI was having its ChatGPT moment in 2022, Joe Scheidler, co-founder and CEO of Helios, was tackling a different kind of challenge: Helping build the White House’s newly authorized cybersecurity office and navigating the complexities of public-private coordination on cyber policies.
His current co-founder, Joseph Farsakh, was also at the State Department, working on Yemen Houthi peace negotiations. The two overlapped in national security discussions and started trading notes on how large language models might transform public policy on a day-to-day level.
On the level the White House operates, critical decisions are often made using a patchwork of tools, spreadsheets, and institutional memory. The founders thought: What if there was a better way to support decision making, one that combined AI-native tools with an understanding of how public policy is decided?
The answer to that question was the idea behind Helios. To make it real, the co-founders brought on Brandon Smith, a long-time acquaintance of Scheidler’s and a machine learning veteran who had worked at Microsoft and Datadog, to lead the technical vision.
“Our unfair advantage is bringing a super unique blend of domain expertise, contacts, and technical expertise to a really important problem,” Scheidler told TechCrunch.
Helios (not to be confused with the payroll/HR management solution, or the climate/economic forecasting product of the same name) emerged from stealth last month with $4 million in seed funding. The round was led by Unusual Ventures, with participation from Founders Inc. and Alumni Ventures, TechCrunch has exclusively learned.
Founders of Helios. (Right to Left) Joseph Faraskh (president), Joe Scheidler (CEO), Brandom Smith (CTO) Image Credits:Helios
Helios’ flagship product is Proxi, an AI-based operating system built for public policy, regulatory affairs, legal, compliance, and government teams, is still in beta. But, Scheidler says, the company is already seeing early traction with workers in federal, state, and local agencies, as well as Fortune 500 companies and startups.
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“We wanted to empower all public policy, legal and compliance professionals with end-to-end automation, deploying sort of a web of secure AI agents that are trained and fine-tuned against really robust public policy data sets to support them on anything from strategic advisement to very sensitive and complex writing products, data analysis and stakeholder mapping,” he said.
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