FiscalNote Holdings, Inc. (NOTEW)

FiscalNote Holdings, Inc. (NYSE: NOTE) was founded in 2013 as a response to a specific problem: for most organizations, understanding and tracking the evolving landscape of laws, regulations, and political trends was difficult and expensive. The company went public in 2022 through a merger with a special-purpose acquisition company and now serves corporations, nonprofits, and government agencies with software and data that illuminate what is happening in the policy world. Today, FiscalNote positions itself at the center of what it calls LegalTech and RegTech (regulatory technology), using artificial intelligence to analyze legislative documents, track policy developments, and forecast the probability and impact of proposed rules.

The founding problem and early focus

Before FiscalNote, tracking legislation and policy changes was largely manual. A government-relations professional at a corporation would subscribe to newsletters, monitor news feeds, attend industry conferences, and maintain personal relationships with legislative staff and lobbyists. It was labor-intensive, subjective, and necessarily limited in scope — a single person or team could only follow a fraction of the relevant policy developments.

When FiscalNote was founded by Timothy Hwang, Gerald Yao, and Jonathan Chen, the ambition was to automate and scale this intelligence gathering. The company built databases of bills, regulations, and legislative voting records, then layered on analysis tools that let clients search, sort, and understand what was happening in legislatures and regulatory agencies. The early product was the FiscalNote platform, a subscription service where clients could track specific legislation, receive alerts when bills were introduced or amended, and see summaries of what each bill was designed to do.

This core product addressed a real need: as regulation became more complex and voluminous, the informational advantage went to those who could synthesize and prioritize the firehose of legislative activity. FiscalNote provided the plumbing.

Expanding the platform and government clients

For years, FiscalNote sold primarily to corporate customers — pharmaceutical companies tracking drug-pricing regulations, financial-services firms monitoring lending rules, energy companies tracking environmental policy. The model was straightforward: larger enterprises paid more, and the company grew by selling more seats and expanding into new industries.

The inflection point came as FiscalNote began working directly with government agencies. Legislators, congressional staff, and executive-branch officials realized that FiscalNote’s tools could help them understand what other agencies were doing, what similar states had implemented, and how the public and interest groups were responding to proposals. By 2023–2024, FiscalNote had announced contracts with all three branches of the federal government — the legislative branch, the executive branch (including federal agencies), and the judicial branch — a significant validation that the company had become a critical infrastructure provider for government decision-making.

The government contracts are high-value: they tend to be large, multiyear agreements with stable budgets and low churn. A congressional office or federal agency that adopts FiscalNote’s tools for legislative analysis is unlikely to switch to a competitor, creating sticky, recurring revenue.

The expansion into local government and AI-powered analysis

A major strategic shift came as FiscalNote recognized that local government policy — city councils, county commissions, school boards — was as complex and consequential as federal policy, but even less well understood. Most corporations had no systematic way to track what was happening in thousands of local jurisdictions. FiscalNote began building out coverage of local governments, and by late 2024, the company announced that its database had grown to encompass over 5 million policy documents across more than 16,000 local governments and school districts in the United States.

Simultaneously, FiscalNote layered artificial intelligence on top of its data. The platform, branded PolicyNote, now uses machine learning to:

• Analyze bills and regulations. An AI summarizes what a bill does, compares it to similar legislation, identifies which industries and constituencies it affects, and flags potential unintended consequences.
• Forecast likelihood. The AI estimates the probability that a bill will pass based on legislative history, sponsor strength, current political alignment, and analogous precedents.
• Track amendments and versions. Legislative language changes constantly; the AI alerts users when important provisions are added or removed.
• Monitor regulatory developments. In addition to bills, FiscalNote’s AI scans regulatory agencies’ notices, proposed rules, and public comments to surface emerging rules and their likely timing.
• Organize by issue. The system surfaces all legislation and regulation related to specific topics (such as AI regulation, healthcare, climate, etc.) in one place, even though they are scattered across jurisdictions.

These AI capabilities have become central to the product. A client can now ask PolicyNote: “Show me every bill or regulation in the U.S. affecting my supply chain” or “What percentage of state legislatures are considering bills like this one?” The system synthesizes vast amounts of text and history that would have taken a human researcher weeks to manually gather.

The business model and customer base

FiscalNote operates a software-as-a-service (SaaS) subscription model. Clients pay annual or multiyear fees for access to the platform and its data. The company differentiates between tiers of service: a basic tier might provide access to federal legislative tracking; higher tiers add state-level, local, and regulatory agency coverage; premium tiers include custom research and direct analyst support.

The customer base spans four primary segments:

1. Corporate enterprise clients — Fortune 500 companies in regulated industries, paying high subscription fees for comprehensive coverage.
2. Government agencies — federal, state, and local government bodies tracking policy developments and regulatory developments.
3. Nonprofit and advocacy organizations — nonprofits, trade associations, and interest groups tracking legislation relevant to their mission.
4. Service providers — law firms, consulting firms, and other professional services firms that use FiscalNote’s data to serve their own clients.

Each segment has different use cases and price sensitivity. Government agencies have stable budgets but slower procurement processes. Corporate clients are price-sensitive but represent larger contracts. Nonprofits and advocacy groups are typically smaller customers but often more engaged and loyal.

Competitive landscape and the AI transition

FiscalNote faces competition from traditional legislative-tracking vendors (such as state-specific services), large consulting firms (which employ analysts to do manual policy research), and increasingly from general-purpose AI tools. A client with access to a large language model could theoretically use it to analyze bills and forecast legislative outcomes. The question is whether FiscalNote’s proprietary database, domain-specific training, and integration with government systems gives it a durable advantage, or whether the company becomes vulnerable to commoditization as AI tools become ubiquitous.

FiscalNote’s response has been to deepen its AI capabilities while expanding its data coverage and maintaining direct government relationships. The announcement in 2025 that FiscalNote had expanded PolicyNote’s API capabilities to allow integration with enterprise and AI-agent workflows suggests the company is positioning itself as infrastructure for the AI era — the API allows other companies’ AI systems to query FiscalNote’s data, which could create new revenue streams and lock-in effects.

Challenges and the path forward

FiscalNote’s growth depends on three factors:

1. Expanding data coverage. As the company covers more jurisdictions, more regulation types, and more of the world outside the United States, the addressable market grows. But each new jurisdiction requires local expertise, relationships with government bodies, and continuous updates.

2. Improving AI accuracy. The value of legislative AI is directly tied to accuracy. If FiscalNote’s AI misses bills, misclassifies their impact, or misforecasts passage, clients lose trust. Continuous training and refinement are essential.

3. Maintaining government relationships. The fact that FiscalNote has contracts with federal government agencies is a strategic asset — it gives the company early visibility into policy trends and serves as proof of value for other customers. But government relationships are fragile and can shift with elections and administrations.

How to research FiscalNote

Start with the company’s 10-K filing (SEC CIK 0001823466), which discloses revenue by customer segment, customer counts, average revenue per customer, and churn rates. These metrics reveal how fast FiscalNote is adding customers and how sticky its customer relationships are.

Monitor quarterly earnings calls for commentary on government-contract wins, expansion into new jurisdictions, and product roadmap announcements. New government contracts and geographic expansion are bullish signals; slowdowns would warrant concern.

Watch for competitive announcements. If large software vendors (such as Salesforce or Microsoft) acquire or build competitive legislative-tracking products, or if OpenAI releases a specialized policy-analysis GPT, the competitive landscape would shift significantly.

Finally, track regulatory developments around AI and data privacy. FiscalNote aggregates and analyzes vast amounts of government data; changes to how government data is classified or made available could affect the company’s ability to serve customers and maintain its informational advantage.