We separate data from processing logic, solving "Grid Blindness" in traditional spreadsheets. Your models, calculations and data analysis become transparent and a readable flow of logic.
Mixes data, formulas, and charts in a single chaotic grid.
Clean logic. Data in variables.
A single cell can hold a million values.
When your data and your formulas live in the same place, the mix of references and ranges burry the logic.
=A2*B2 + C2/D2 where you
don't know where A, B, C, or D
come from.
The "Clean Room" Architecture.
Users only interact with the processing flow. The raw data is hidden.
| revenue = {sales_data,0}.sum() | |
| expenses = {operational_costs,0}.sum() | |
| net_profit = revenue - expenses |
Anyone can read this immediately. No need to scroll through thousands of rows.
Raw data is stored in background variables. It stays clean and structured.
With data hidden in vectors, your visible sheet contains only the math. You can now see the trees in the forest.
Result: 50% faster model debugging.
Use intuitive commands like {var,0} to reference
data.
The logic is
self-documenting.
Result: Key Person Risk eliminated. Onboarding time reduced by 70%.
LLM's (A.I.) can now understand your structure. No more scanning thousands of rows to find the formula.
The power of coding with the simplicity of a spreadsheet.
Build complex financial models. Audit every line item. Share with stakeholders without revealing sensitive raw inputs.
Solve ODEs, process vector data, and visualize results in real-time without writing Python scripts.
Simulate systems, perform optimizations, and manage vectorized sensor data in a clean, readable interface.
Prepare data for ML models. Train small neural networks (coming soon) directly in the browser using build-in functions.
All regular math expressions are available. For example: exp, sqrt, sin, sinh, cos, ln, log, logical comparison ==, !=, || and &&