Random assumptions. Broken formulas. Version chaos.
Stop patching together pre-feasibility studies in broken spreadsheets.
We give you one defensible source of truth — integrated benchmark data, fully traceable assumptions, and outputs built to survive investment committee scrutiny.
preFeasibility — Built for scrutiny | Simple for developers
We get it — most teams run early feasibility in Excel, and it gets you far.
Turning those models into traceable, consistent, benchmark-backed outputs that survive serious review — internal and external — is where the real effort goes, every time.
We help close that gap — with one structured, data-driven platform built for scrutiny.
Every result is benchmarked across six dimensions against the country median — LCOE, CAPEX, capacity factor, OPEX, WACC, and project lifetime. You see not just where your cost lands, but which assumptions are driving the gap. Built from IRENA, Lazard, and BNEF data, updated annually.
Knowing your LCOE is $52/MWh is useful. Knowing it is 15% below the country median because your capacity factor is above the regional range — that is what a serious analyst needs before a client meeting.
We estimate LCOE, AEP with 25-year degradation, Project IRR, NPV, breakeven PPA, and CO₂ avoided. Three parallel scenarios — conservative, base, and optimistic — are computed simultaneously, so you are prepared for any question in the room.
Project IRR only — equity IRR requires debt sizing, DSRA, and tax equity structures.
Every saved run is a permanent record — inputs, outputs, and benchmark position. Select any two or more runs and compare them in a structured table: LCOE, IRR, NPV, CAPEX, capacity factor, and country percentile side by side. Track how a project evolves across assumption revisions, or evaluate one site against another in a different market.
Designed for the professional managing multiple projects or iterating through scenarios. Available at the $50 wallet threshold.
As inputs are entered, we compare them against country norms in real time. If CAPEX is unusually low for the region, or capacity factor sits outside the observed range, a flag appears inline — before the model runs. The user decides whether to proceed, with full visibility of the risk.
One of the most common sources of credibility loss in early-stage analysis is an assumption that looked reasonable in isolation but was inconsistent with the market.
Let’s make your next project assessment smarter and fully traceable — at a fraction of the cost of outsourcing. Spend real time and money only when the site actually warrants it.