Start estimating economic viability in hours, not months.
The TEA Conductor guides entrepreneurial climate scientists from a blank sheet to a working model — grounded in the TEA Commons data repository, keeping you in the driver's seat.
Understand why we're building this → Read the TEA Commons Impact Memo
A guided workflow, step by step.
From technology setup through process flow mapping, economics, and sensitivity analysis, each stage builds on the last, with the data repository surfaced in context throughout.
The goal isn't just a completed and actionable TEA, it's a scientist who understands their own economics. The co-pilot asks questions rather than producing answers, surfaces the reasoning behind every data point, and creates the productive friction that makes the analysis stick so the TEA you built is a mental model.
The TEA Conductor: our step-by-step guided workflow
Our AI principles:
Every number is auditable. Inputs are sourced, cited, and inspectable: every number traces back to a hardcoded datapoint from a trackable source, or is calculated through deterministic formulas. AI surfaces values; it does not generate them.
The math is deterministic. We minimize the surface area of AI-derived input. Models are fixed systems of equations — like a robust spreadsheet, the same inputs always produce the same outputs. AI may help assemble a model, but its output is always explicit equations that can be inspected line by line.
Canonical process flows as the foundation. The system anchors in the library of validated reference industrial processes. Novel technologies are handled by identifying the closest reference class and customizing from there, which keeps the probabilistic surface small and the auditable surface large.