About Celvanto
Appliance cost analysis, democratized
Celvanto uses Energy Star product data, DOE efficiency standards, EIA energy pricing, and DSIRE incentive databases to help you find the appliance that actually minimizes your total lifetime cost -- purchase price, energy, maintenance, and incentives included.
The Problem
Every year, 20 million Americans buy a major appliance based on sticker price alone. But the purchase price is only 20-30% of the true cost. Energy consumption over 10-20 years, maintenance, repair probability, and available incentives (IRA tax credits, state rebates, utility programs) all determine what you actually pay. A cheap furnace can cost thousands more than a premium heat pump when you account for the full lifecycle.
Our Approach
We ingest efficiency ratings from Energy Star, energy prices from EIA, incentives from DSIRE, and equipment lifetime data from DOE. For each product, we run 10,000 Monte Carlo simulations of future energy prices, model maintenance costs using Weibull failure distributions, and stack all available incentives. The result is a complete lifecycle cost distribution -- so you can choose the appliance that matches your budget and your risk tolerance.
Our Values
Data Integrity
We use only authoritative Energy Star, DOE, and EIA data. Every cost estimate traces back to published federal datasets -- no proprietary black boxes.
Accessible Intelligence
Appliance lifecycle cost data has been locked behind manufacturer marketing. We make the math accessible to every homeowner.
Honest Assessment
We do not sugarcoat costs. Our Monte Carlo simulations show expected costs and worst-case scenarios so you can plan for both.
Developer-First
Every feature available to consumers is also available through our REST API. Build appliance TCO analysis into your own applications.
Part of Smart Technology Investments
Celvanto is a product of Smart Technology Investments LLC, a research-driven company building decision intelligence tools that help consumers make better financial decisions using data that was always available but never accessible.
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