Glassbox, a Toronto-based fintech startup, has secured USD 1.2 million in pre-seed funding to modernize financial modeling through AI-powered workflows. The funding round was led by FinTech Collective (New York) and StandUp Ventures (Toronto), with participation from Watertower Ventures (Los Angeles). The fresh capital will help expand Glassbox's team and bring its AI-compatible financial analysis platform to market.
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Addressing Finance's Spreadsheet Problem
"While other industries have begun embracing real-time collaboration tools and AI-powered assistants, finance teams have been left with little more than bigger, more complex Excel files," the company said.
Finance teams have long relied on cumbersome spreadsheets and manual processes. Glassbox aims to change that with its proprietary framework, FinScript, which replaces complex spreadsheet formulas with natural language instructions optimized for large language models (LLMs). According to the company, this approach enhances speed, accuracy, and transparency while remaining compatible with Excel-based workflows.
Glassbox's FinScript
"Agentic workflows are generating a lot of buzz, but corporate finance remains hindered by manual processes and fragmented, context-poor data trapped in spreadsheets, limiting their potential," said Allison Harris, Glassbox's CEO and co-founder. "Our goal is to build smarter, more transparent tools that will truly enable finance professionals to responsibly leverage AI at scale."
"Glassbox's solution is centered around a new framework it calls FinScript. Rather than building financial models and analysis with traditional spreadsheet formulas, users can input plain text instructions that align with large language models' (LLMs) capabilities for processing written information. This approach adds context and structure to data and enables faster, more auditable analysis while maintaining compatibility with existing Excel-based processes," the company explained.
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"FinScript bridges the gap between human expertise and LLMs' power," said Ian Kennedy, CTO and co-founder. "FinScript transforms complex financial models into simple, auditable instructions, allowing teams to work faster and smarter without compromising on rigor or transparency."
Glassbox claims FinScript enables even junior analysts to evaluate deals up to five times faster than experienced Excel users, significantly reducing the risk of costly errors.
AI-Powered Financial Modeling
"Finance is uniquely positioned to benefit from AI, but spreadsheets are not built for this shift," said Brooks Gibbins, co-founder and Managing Partner at FinTech Collective. "You can think of Glassbox as the financial modeling equivalent of GitHub for code management or Notion for content creation - bringing 0-1 structure, traceability, and collaboration to complex financial workflows. By staying fully compatible with Excel, Glassbox enables finance teams to harness the power of AI without disrupting their existing processes."
"The applications of Glassbox are remarkably broad," Harris noted. "From investment banking and private equity to hedge funds, FP&A, and insurance, Glassbox is designed to maintain flexibility, making it ideal for a wide range of financial analysis use cases."
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Scaling Up
The company has been operating in stealth mode for 18 months, running private beta programs with industry executives. With the funding secured, Glassbox says it is opening its waitlist to a broader audience and plans to scale distribution later this year.
The company says its spreadsheet platform is poised to transform how financial professionals analyze deals, collaborate, and make decisions— all without leaving Excel behind.
Glassbox
Founded in 2023 and headquartered in Toronto, Glassbox says it is on a mission to empower capital markets and investment professionals with cutting-edge tools that deliver unmatched productivity gains, reduce errors, and harness the power of AI. "By reinventing the spreadsheet as an AI-compatible platform, Glassbox aims to make financial analysis faster, smarter, and more transparent," it said.
