Think clearly about your technology's path to market.
You don't need to be an economist. You need the right data, the right framework, and guidance from people who've done this before.
Where are you in your TEA journey?
Jump to a section below ↓Understand what good looks like.
Techno-economic analysis (TEA) is how you figure out if your breakthrough can actually become a product the world can afford. The good news: you don't need an MBA or a consultant. You need a directional understanding of your economics — and that starts with knowing what "good" looks like at your stage.
TEA-Readiness Levels
| Stage | Focus | What "Good" Looks Like |
|---|---|---|
| TRL 1–3 | Order-of-magnitude economics | Process flow diagram, key cost drivers identified, rough unit economics with wide ranges (±50%) |
| TRL 4–5 | Directional decision-making | Full TEA model with sourced assumptions, sensitivity analysis on top 5 drivers, ±30% accuracy |
| TRL 6+ | Investment-grade analysis | Validated assumptions from pilot data, Monte Carlo simulations, detailed capex/opex breakdown |
Public TEA Example
We built a fully public techno-economic analysis with Homeworld Collective — a bio-mining startup turning mine waste into critical minerals. Explore the model, read the methodology, and see what a good early-stage TEA looks like.
Bio-Mining TEA Model
The full spreadsheet model — open-access, annotated, ready to explore.
TEA Guide
A step-by-step walkthrough of the model structure, assumptions, and methodology.
The bottleneck isn't modeling — it's finding data you can trust.
Our survey data confirms what we've seen across 1,500+ coaching hours: finding trustworthy data is the single hardest part of building a TEA. Teams independently research the same data points — a startup in one city spends 10-15 hours finding capex data that another team halfway around the world researches at the same time.
Open Full RepositoryCurated Data Sources
NREL Annual Technology Baseline
Comprehensive cost and performance data for electricity generation technologies.
DOE Hydrogen and Fuel Cell Technologies Office
Technical targets, cost projections, and production pathway data for hydrogen technologies.
IEA Energy Technology Perspectives
Global energy technology cost and deployment data across sectors and scenarios.
Chemical Engineering Plant Cost Index (CEPCI)
Industry-standard index for adjusting process plant construction costs over time.
USGS Mineral Commodity Summaries
Annual data on production, imports, exports, and prices for over 90 mineral commodities.
AI and validated data can finally democratize expert-level TEA support.
A co-pilot tool that guides you through building a TEA in the context of your workflow — grounded in the validated data repository to prevent hallucination, encased in a calculation engine to eliminate LLM-related errors.
AI-as-Analyst
Speeds up reference class development with human-in-the-loop review.
AI-as-Librarian
Surfaces relevant data points in-context and explains concepts.
AI-as-Coach
An infinitely patient guide that enables adaptive learning without doing the work for you.
You don't have to do this alone.
Practitioner Network
Find domain experts who can help validate your assumptions and review your model.
Workshops & Events
Regular sessions on TEA methodology, industry-specific deep dives, and peer learning.
Peer Community
Connect with other scientists doing TEA work — share frameworks, debate assumptions, learn together.