Building a compiler, IDE, and serverless runtime for spreadsheet-style logic

There’s a hidden crisis in every company

Watch any operations or finance team for a day and you'll see some scary stuff:

• Copy-pasting from emails into Excel
• Using cmd + f to one-by-one go through a long list of find/replace rules
• VLOOKUPs referencing random Google Sheets that break when someone renames a column
• Eyeballing PDFs to manually enter data
• Hardcoding values when systems don't talk to each other
• Redoing everything when an exec questions why a number doesn't match

These aren't edge cases. This is how critical business processes like inventory reconciliation, GL mapping, and PO matching actually work at most companies. It might sound crazy but it’s actually rational. These processes move too fast, are too full of messy data, and rely too much on subject matter expertise to be handled by code.

The subject matter expertise these teams have is incredible. They know exactly what needs to happen, they just lack the tools to make it happen efficiently. So they go back to their spreadsheets.

We tried to solve it better than traditional solutions

A lot of companies have tried to solve this. RPA tools break when UIs change. No-code platforms hit walls with real-world data complexity. Traditional BI tools can't handle the messy, exception-filled processes that define operations work.

At Parabola, we realized we needed to build something fundamentally different. Not just another no-code tool, but a reimagining of an entire engineering stack designed specifically for how business teams think about data.

• ‍A domain-specific language that operates on data the way someone thinks in spreadsheets, not SQL or Python. When an ops person says "match these two lists but ignore blanks and typos," it just works as expected.‍
• A visual IDE with live debugging where every transformation shows instant previews. Users see exactly what's happening to their data at each step without having to wait until the end to “run and pray”‍
• A schema-less calculation engine that handles CSVs with 47 columns today and 53 tomorrow, with five different date formats and random strings. Because that's reality in operations.
• Production-grade infrastructure including simple abstractions for statefulness, serverless deployment, inbound email triggering, comprehensive logging, and exception handling that actually helps non-technical users fix what went wrong.

But the technology just wasn’t there yet

Building all of this got us partway there. Forward-thinking companies like Brooklinen, Flexport, and On Running started solving their messiest problems in days instead of months. But we were still limited by the number of power users who could translate their knowledge into flows.

Seven years in, and most people were still going back to spreadsheets.

Then this year, LLMs reached a tipping point. And the features we’ve been able to build have changed everything.

• An AI agent that actually understands operations. It's trained on thousands of real workflows and can build with you or for you. Ask it to "reconcile these invoices but flag anything over 5% variance" and it knows exactly what you mean.
• Dynamic code generation that adapts. Instead of brittle scripts, Parabola generates fresh code on the fly that updates when your data shape changes. The code is visible, auditable, and modifiable—no black boxes.

The key insight: AI works when it has the right foundation. Without our domain-specific language and tooling, this would just be another chatbot that generates broken Python. With it, ops teams are now "vibe coding" their way to production-grade automations.

What this means for technical teams

We launched these new features last week, and the response has been epic. But here's why you should care if you’re coming from a technical background.

• Fewer “quick python scripts”, more strategic work. When ops teams can solve their own problems, you stop being the bottleneck for every data transformation request.
• Auditable, version-controlled processes. Everything built in Parabola has a clear audit trail. No more mystery Excel macros or undocumented processes.
• Faster iteration cycles. Business teams can prototype and refine their own solutions at the speed they need.
• Scale without hiring. One ops person with Parabola can do the work that previously required a team of analysts or constant engineering support.

In 2025, operations teams need to work like engineering teams—with repeatability, scale, and automation.

I’d love to hear what you and your teams think. You can try Parabola for free, or see some example flows.