Building Ramp Sheets: How SpreadJS Helped Ramp Labs Build an AI-Native Spreadsheet Experience

Case Study  |  July 27, 2026  |  Ramp Labs

Industry Context

Ramp Labs is the AI research and experimentation team within Ramp’s Applied AI organization. One of their latest projects includes Ramp Sheets. It is an AI-native spreadsheet that helps finance teams and operators automate modeling, reporting, reconciliation, and analysis. Built for financial workflows but flexible enough for a wide range of spreadsheet tasks. Ramp Sheets combines AI-powered assistance with the functionality users expect from modern spreadsheets.

The idea for Ramp Sheets grew from an exploratory effort to better understand and streamline Ramp's internal accounting workflows; specifically the month-end close process. As the solution evolved, the Ramp Labs team recognized that finance professionals expected the same rich functionality they were accustomed to in spreadsheet apps like Microsoft Excel and Google Sheets. During their evaluation of different JavaScript spreadsheet components, they quickly gained an appreciation for just how extensive those expectations really were. Meeting them required a feature-rich, dependable spreadsheet solution.

The Ramp Labs team found that SpreadJS provided the familiar spreadsheet experience their users expected. Allowing their engineers to focus on building AI-powered capabilities instead of recreating core spreadsheet functionality. To learn more about their efforts and development process, we spoke with Ramp Labs Research Engineers Ben Geist and Alex Henkel.

The Challenge: Building an AI Product on Top of Familiar Spreadsheet Workflows

Finance professionals think in spreadsheets, it’s their love language. Spreadsheets remain the primary tool for modeling, reporting, analysis, and much more. Before Ramp Sheets, many of these tasks were performed manually, requiring teams to spend significant time preparing, updating, validating, and analyzing workbooks.

Ramp Labs saw an opportunity to bring AI directly into those existing workflows. Rather than asking these long-time experienced users to adopt an entirely new way of working, why not just create a spreadsheet based application? To do this, they knew they had to deliver the familiar spreadsheet experience these finance professionals rely on every day.

“You can't ship something if it doesn't provide an Excel-like experience. If you want to have a good user experience, you need to give them what they're used to.” – Alex Henkel

Why SpreadJS: Spend Engineering Time Where It Matters

Rather than spending years recreating core spreadsheet capabilities their users expected, the Ramp Labs team looked for a proven JavaScript spreadsheet component. The team needed a developer-friendly solution that could deliver the rich spreadsheet functionality, without consuming valuable engineering resources. After evaluating their options, they chose SpreadJS.

"SpreadJS enabled the core spreadsheet interface that Ramp Sheets is built around. Rather than being an additive feature, it served as the foundation for the primary user experience." – Ben Geist

Instead of investing time recreating spreadsheet behavior, they could focus on building the AI intelligence behind Ramp Sheets.

"SpreadJS allowed us to avoid spending significant engineering time rebuilding core spreadsheet functionality on the front end. Instead, we were able to focus our efforts on the agentic system, backend infrastructure, and performance." – Ben Geist

Ramp Sheets Application Screenshot | Built using SpreadJS, a JavaScript Spreadsheet Component

Using SpreadJS, Ramp Labs quickly delivered the familiar spreadsheet experience their users expected. With built-in support for formula support, charts, keyboard shortcuts, context menus, and other spreadsheet features. Allowing their team to easily provide a production-ready spreadsheet.

"One of the nice things about SpreadJS is that we could just plug it into our frontend and get all of that functionality directly out of the box without having to develop it ourselves. Spreadsheets are complicated… and I don't want to build them myself." – Alex Henkel

Technical Spotlight: Formula Evaluation Was Harder Than Expected

The Ramp Labs team noted that formula evaluation is one of the most complex parts of delivering a true Excel-like experience. Finding a component and workflow to support the vast number of formulas, parameters, and edge cases users expect is far more difficult than it appears.

“There's so many different formulas, and everyone expects all of them to work. There's so many different options and parameters. Having to build that ourselves would have been very, very difficult. Having firm evaluation, fast on the client, has definitely been very useful.” – Alex Henkel

Initially, the team experimented with evaluating formulas in different environments, including their Python backend. However, keeping multiple calculation engines synchronized introduced unnecessary complexity and inconsistencies between the frontend and backend.

Instead, the Ramp Labs team standardized on the SpreadJS formula engine, ensuring calculations behaved consistently across the application while simplifying their overall architecture.

"If you're building a spreadsheet agent, do formula evaluation on the client. It's way easier! Use the existing SpreadJS formula evaluation. Don't try and cobble something together." – Alex Henkel

For Alex, this was one of his biggest recommendations for other developers building spreadsheet-based applications:

"Formula evaluation is much harder than you think it is… Always keep it in one spot and just use SpreadJS because it's what the UI expects."

The Solution & Business Impact

With a dependable spreadsheet foundation in place, Ramp Labs could focus on building their own custom trained AI model, called Fast Ask, to help power the AI prompted spreadsheet requests. For example, given a question like “What was the revenue from March to May?”, Fast Ask will navigate the existing workbook, read the relevant ranges, and returns a compact answer for the main agent to use.

Using SpreadJS and Fast Ask, Ramp Sheets was born, helping finance teams reduce spreadsheet work from hours to minutes and has been used to create thousands of spreadsheets each month. Flexible enough to handle tasks like project planning, building schedules, helping college students with accounting homework, and much more.

“One of the nice things about AI is that it meets you exactly where you are. So you don't need necessarily to super fine-tune every single interaction to a specific use case. The assistant can do anything in the spreadsheet, and we try and enable it to be as generally potent as possible.” – Alex Henkel 

Case Study Summary

“It's a return to the core of what users actually need. All the extra stuff you would have built for the user experience, you don't need that anymore. Now users can prompt an AI agent and it can do tasks for them.”  – Alex Henkel

As AI continues to reshape financial software, Ramp Sheets demonstrates that the future isn't about replacing spreadsheets, it's about making them smarter. By using SpreadJS as the foundation for the user experience, Ramp Labs was able to focus on delivering the AI-powered capabilities that sets Ramp Sheets apart.

Learn More About SpreadJS

SpreadJS is a comprehensive JavaScript spreadsheet that provides a complete Microsoft Excel-like experience, even for your Excel power users, including charts, tables, shapes, sparklines, conditional formatting, functions and filtering and so much more.  With support for seamless Excel import and export, you can easily integrate your existing spreadsheet data and create and share reports without any dependency on Microsoft Excel.

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