Financial Technology Firm

Company Background

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A leading global financial technology firm operates a high-scale data platform that aggregates public company earnings information into a comprehensive, queryable database used by investment professionals. As the volume and complexity of financial data grew, the firm recognized an opportunity to revolutionize how analysts interact with their data. Through a competitive evaluation process, they selected Stride to build an AI-powered solution designed to make financial modeling faster, more intuitive, and dramatically more efficient.

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Challenge

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Financial analysts spend countless hours manually extracting data from proprietary platforms and formatting it into complex Excel models. The firm needed a solution that would allow analysts to query their extensive database using natural language, automatically generate properly formatted financial models, and seamlessly integrate into Excel—the analyst's primary workspace. The system had to understand nuanced financial terminology, handle diverse modeling scenarios, and deliver accurate, ready-to-use data without requiring technical expertise from users.

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Solution

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Stride designed and built a custom AI-powered Excel plugin that fundamentally changes the financial modeling workflow. Powered by a sophisticated Large Language Model (LLM), the tool enables analysts to use simple natural language queries to generate complex, multi-period financial models instantly.

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The system works seamlessly within the existing workflow: analysts type a query, the AI processes the request to understand the specific intent and parameters, retrieves the relevant figures from the firm's comprehensive database, and automatically populates properly formatted data directly into the spreadsheet. The system handles the heavy lifting of mapping financial terminology and structuring the output into analyst-ready formats.

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This agentic AI architecture acts as an intelligent intermediary between the professional and the raw data. By utilizing a continuous learning loop based on user feedback, the system expands its understanding of complex terms and edge-case scenarios over time. Currently in beta, the platform is revealing high-value use cases beyond basic modeling, including automated comparative analysis, trend identification, and rapid scenario planning.

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Outcomes

• Order-of-Magnitude Velocity: Transforms labor-intensive financial modeling from a multi-hour manual process into a task completed in minutes, allowing analysts to pivot from data entry to high-value insight generation.
• Seamless Workflow Integration: Eliminates the "context switching" tax by embedding agentic AI directly into Excel, enabling professional-grade modeling through simple natural language queries.
• Augmented Analytical Rigor: Establishes a scalable foundation for "agent-ready" financial data, empowering analysts to perform complex comparative analysis and scenario planning at unprecedented speeds without sacrificing accuracy.

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