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InScope Secures $14.5 Million Funding to Transform Financial Reporting Through AI-Driven Last-Mile Automation

Summarized by NextFin AI
  • InScope, a fintech startup, secured $14.5 million in Series A funding to automate financial statement preparation, targeting the error-prone final stage of reporting.
  • The platform aims to eliminate manual checks by automating arithmetic verification and cross-document tie-outs, significantly increasing its customer base by five-fold in the past year.
  • InScope's AI-driven approach offers transparency in financial reporting, addressing CFO concerns over accuracy under Sarbanes-Oxley requirements.
  • The startup is positioned for growth in ESG reporting and aims to become essential for modern CFOs, potentially disrupting legacy platforms.

NextFin News - InScope, a financial technology startup founded by former accounting operators, announced on February 20, 2026, that it has secured $14.5 million in Series A funding to automate the labor-intensive processes of financial statement preparation. The investment round was led by Norwest Venture Partners, with significant participation from Storm Ventures and existing backers including Better Tomorrow Ventures and Lightspeed Venture Partners. Based in the United States, InScope aims to utilize this capital to scale its engineering team and expand its enterprise footprint, specifically targeting the "last mile" of financial reporting—the final, error-prone stage where raw data is transformed into compliant 10-Ks, 10-Qs, and audit-ready reports.

The company was founded by Mary Antony and Kelsey Gootnick, both of whom served as controllers and finance leaders at high-growth firms such as Flexport and Miro. According to Antony, the platform does not seek to replace the accountant but rather to eliminate the "spreadsheet hell" that characterizes month-end and quarter-end closes. By automating arithmetic verification, cross-document tie-outs, and narrative alignment, InScope addresses the specific pain points that lead to late-night manual checks and costly auditor revisions. The startup has already demonstrated significant market fit, reporting a five-fold increase in its customer base over the past year, including adoption by major accounting firms like CohnReznick.

The timing of this funding is particularly strategic given the current regulatory and economic climate under U.S. President Trump. As the administration emphasizes domestic corporate efficiency and streamlined reporting, the demand for tools that reduce the compliance burden has intensified. Financial reporting remains a massive software category; for context, industry incumbent Workiva reports annual revenues exceeding $600 million, while Donnelley Financial Solutions operates near the $1 billion mark. However, these legacy platforms often function as sophisticated document editors rather than intelligent automation engines. InScope’s entry into this space represents a shift toward AI-native solutions that understand the underlying GAAP (Generally Accepted Accounting Principles) logic rather than just the formatting of the output.

From an analytical perspective, InScope’s success hinges on its "human-in-the-loop" architecture. In the risk-averse world of corporate finance, black-box AI is a non-starter for CFOs who must personally certify the accuracy of financial statements under Sarbanes-Oxley (SOX) requirements. InScope’s platform provides transparent change logs and justification trails, allowing accountants to review AI-generated flags for inconsistent disclosures or math breaks. This deterministic approach to AI—where the system identifies errors based on rigid accounting rules rather than creative generation—is what separates viable fintech tools from experimental prototypes. Data from Gartner suggests that finance teams still spend up to 25% of their time on routine reporting; InScope’s ability to reclaim 20% of that peak-period time offers a clear ROI for enterprise customers.

Furthermore, the involvement of Norwest Venture Partners, which has previously backed fintech giants like Plaid and Credit Karma, suggests a broader trend: the institutionalization of AI in the back office. As global reporting standards converge and the SEC continues to mandate complex disclosures like Inline XBRL, the margin for manual error is shrinking. InScope is positioning itself as the connective tissue between ERP (Enterprise Resource Planning) systems and the final filing. By integrating directly with data sources and applying policy-aware drafting aids, the platform reduces the "cycle time" of a report—the number of times a document must pass between the finance team, the legal department, and external auditors.

Looking ahead, the trajectory for InScope and the wider financial reporting automation sector is one of deep integration. We expect to see InScope expand into ESG (Environmental, Social, and Governance) reporting, where narrative-data consistency is notoriously difficult to maintain. As U.S. President Trump’s policies continue to shape the corporate landscape, companies will likely prioritize tools that offer both defensive compliance and offensive efficiency. The ultimate winner in this space will be the platform that becomes the "system of record" for the audit trail itself. If InScope can maintain its current growth trajectory and successfully navigate the complex enterprise sales cycles, it may well transition from a niche automation tool to an essential component of the modern CFO’s tech stack, potentially forcing incumbents into defensive acquisitions or rapid internal pivots.

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Insights

What are the core technical principles behind InScope's AI-driven automation?

How did InScope's founders leverage their background in accounting to create the platform?

What is the current market situation for financial reporting automation tools?

What feedback have users provided regarding InScope's platform?

What recent updates have occurred in the financial reporting automation industry?

How do regulatory changes affect the demand for InScope's automation solutions?

What are the anticipated future developments in financial reporting automation?

What challenges does InScope face in scaling its platform?

What controversies exist around AI utilization in financial reporting?

How does InScope compare to legacy financial reporting platforms like Workiva?

What historical cases illustrate the evolution of financial reporting automation?

What impact do AI-native solutions have on the compliance burden for companies?

How does InScope's 'human-in-the-loop' architecture enhance accountability?

What role does Norwest Venture Partners play in InScope's growth strategy?

How might ESG reporting influence the future of financial reporting automation?

What long-term effects could InScope's growth have on the fintech landscape?

What are the potential risks associated with relying on AI in financial reporting?

How does InScope address the issue of data consistency in financial reporting?

What factors contribute to InScope's rapid customer base expansion?

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