Financial Models Should
Be Engineered
Write models in Python, deliver as Excel with real formulas.
Versioned. Connected to data. AI‑readable. Human‑transparent.
The engine is now open source.
$ pip install modeleonIf Modeleon resonates — a GitHub ⭐ helps more people find it.
The problem
There is no proper tool for
financial model automation yet.
of Excel models contain errors.
of CFOs say correcting errors and chasing data impairs strategic decision-making.
version control. No deep dependency graph. No testing. Models live in one person's head and die when they leave.
of finance teams still rely on Excel even when they have planning software.
The pattern
Every other data workflow is already engineered.
Financial modeling isn’t.
Data ingestion, transformation, storage, visualization. All versioned, tested, automated. But the financial model, where the actual decisions happen, is still a spreadsheet someone emailed.
Data Transformation
Analytics Engineering
dbt
Versioned, tested, documented
Data teams version and test every SQL query. Financial models have no version history at all.
Infrastructure
Infrastructure as Code
Terraform
Automated, repeatable, auditable
DevOps teams describe servers in code and deploy with one command. Finance rebuilds the same model from scratch every quarter.
Financial Modeling
Financial Model Engineering
Modeleon
The most valuable layer in the stack
Where decisions actually happen. Still unengineered. It's time.
What we’re building
The first platform built for
Financial Model Engineering.
Python → Excel with real formulas
Write revenue = price * volume in Python. Get =B4*B5 in the Excel cell. Not values. Live formulas.
AI that reads your logic
AI reasons about the model's dependency graph, not flat cells. Structured code is fundamentally easier for AI to understand than spreadsheets.
Version control, built in
Every model is code. Git-diffable. No more Q3_Budget_v7_FINAL_v2.xlsx.
Connected to any data
Models read from any source: data warehouses, ERPs, APIs, databases. No manual copy-paste.
Advanced analytics
Monte Carlo, optimization, time-series forecasting, machine learning. The full Python ecosystem inside your financial model.
Audit every number
Every output traces to a formula. Every formula traces to an assumption. Auditors, boards, and regulators can verify.
Financial models deserve engineering.
Read the full case for why financial models should be engineered. And why now.
Read the ManifestoWe’re building it.