Govtech Ventures | Investment Thesis & Preferences

01Investment Thesis

We back early-stage govtech founders building across the public-sector stack, from citizen services to critical infrastructure protection, combining strategy, capital, and deep government sales expertise to help founders build scalable foundations, accelerate growth, and reach meaningful exits.

Exclusion Criteria

No federal or defense contracting plays; skeptical of speculative, standalone AI tools not grounded in messy real-world government data.

02Investment Team

RS

Rachel Stern

Founding & Managing Partner

03F4 Research Brief

Govtech Ventures Research

Investment Thesis

Govtech Ventures is a solo-GP venture fund founded in 2024 by Rachel Stern to back early-stage founders modernizing state and local government. The thesis targets three failure modes in the public sector: outdated systems that run on legacy, paper-based processes; siloed data that prevents agencies from sharing information or collaborating across departments; and limited citizen engagement, where residents lack trustworthy, real-time channels to interact with their government. Rachel treats government technology as fundamentally distinct from federal or defense technology. Roughly 5,000 cities and 3,000 counties manage the actual mechanics of American civic life, operating on one-to-five-year election cycles rather than the decades-long horizons of federal procurement. She avoids the Department of Defense and federal government entirely.

The firm looks for defined total addressable markets, gross margins near 80%, and net revenue retention above 100%. Because government customers rarely churn once a tool is embedded in a workflow, Rachel underwrites for durability and "stickiness" over blitz-scaling. She explicitly gives founders optionality: portfolio companies are not pushed toward unicorn outcomes, and Rachel is equally supportive of a founder building a $50M-$500M business with a three-year exit horizon as one chasing a billion-dollar outcome.

Stage Focus

Govtech Ventures invests at pre-seed and seed, occasionally seed-plus. It is one of the only dedicated solo-GP funds focused exclusively on govtech.

Check Size

Typical checks range from roughly $500K to $3M, consistent with a $15M fund investing across a concentrated early-stage govtech portfolio.

Lead Tendency

Rachel frequently invests alongside other seed investors (e.g., CreativeCo Capital and BarronKent Ventures in Madison AI's seed round) rather than exclusively leading rounds. Given the fund's modest check sizes, she often plays a value-add participant role, though she has been the first institutional or first outside check for companies like PayIt and Ignatius.

Recent Activity

The firm closed the first tranche of its $15M inaugural fund in December 2024, with a second close following in spring 2025. It has continued deploying into 2026, most recently backing Blue Voice, an AI assistant platform for police officers, in September 2026, and participating in Madison AI's seed round in December 2025. Rachel also runs a weekly video series and Substack ("Stern Talk") publishing govtech go-to-market and fundraising guidance for founders.

Portfolio Highlights

Fund I's current portfolio includes YCurb (digital curb-management infrastructure for cities and campuses), Madison AI (an AI knowledge engine for local government staff reports, procurement, and code lookup, co-created with Washoe County, NV), Blue Voice (a closed-loop AI assistant for police officers, used by 225+ agencies), and Paralign Health (community paramedicine and in-home preventative care for rural and underserved populations).

Before and alongside the fund, Rachel built a broader personal track record of angel investments and advisory relationships in govtech, including PayIt (government payments and CX platform, her first institutional check), Ignatius (grants management and disaster-recovery software, acquired by OpenGov in February 2025), OpenGov (enterprise resource planning for governments, acquired by Cox Enterprises for $1.8B in February 2024), Polco (community engagement and survey platform), Rep'd (AI video communications platform for city governments, founded by ex-Twitter employees), Civio (an AI operating system for B2G revenue teams, incubated by Andrew Ng's AI Fund), Ladris (disaster evacuation modeling and decision support for emergency planners), ManyBond (a platform opening tax-exempt municipal bonds to retail investors), Streamline (special-district government software, where Rachel served as Chief Strategy Officer), Opt Health, Kora Power, and Nexa.

Team

Rachel Stern, Founding & Managing Partner — Nearly 15 years across lobbying, operations, and investing. Spent a decade as a lobbyist and strategist helping pass more than $3 billion in legislation across 46 states, and advised category-defining companies (Lyft, Zoom, Square, Hims & Hers) on navigating government regulation. Previously Chief Strategy Officer at Streamline. First investor in PayIt and Ignatius. Serves on the boards of CivStart and GFOA Innovation, and mentors at FedTech connecting federal technologies to state and local use cases.

Decision Process

Govtech Ventures is a solo-GP fund: Rachel makes investment decisions independently. She describes spending roughly a month working directly with a founder before committing capital, coaching go-to-market strategy and reviewing pitch materials to confirm the founder is coachable — a requirement she considers essential given how costly mistakes are when navigating state and local bureaucracy.

Founder Preferences

Rachel looks for founders with the grit to survive long procurement cycles (six to eighteen months is typical) and who have already had at least 50 conversations with potential government customers before building product. She wants early traction defined as three pilots or one solid signed contract, then uses her LP network of GovTech operators and family offices to help scale from one contract to twenty. She is skeptical of speculative, standalone AI plays, preferring traditional SaaS platforms with integrated AI functionality, since she views most government data as too messy ("trapped in filing cabinets, legacy Microsoft 2003 systems, or analog forms") for AI alone to be transformative.