OwnWatt is a behavioral intelligence platform that helps residential households make coordinated, optimized energy decisions across solar, battery, EV charging, and time-of-use pricing. By profiling how each household actually decides, OwnWatt delivers personalized recommendations that reduce costs and enable reliable program participation for utilities and OEMs. The platform requires no hardware, using scenario-based assessments and real-time decision logging to turn fragmented device apps into one unified action plan.
Funding
Funding not disclosed
Founders
Product
Problem
Residential energy management is fragmented across multiple device apps, leaving households with dozens of uncoordinated daily decisions around solar output, EV charging, battery state, and time-of-use pricing. Most households don't understand their own tradeoffs between comfort, cost, and control, and no single layer coordinates these decisions—leading to EV charging at peak rates while batteries sit idle and solar exports at low prices.
Solution
OwnWatt provides a decision intelligence platform that optimizes household energy behavior without requiring any hardware. The platform conducts a household energy audit to surface specific gaps in rate plans, device efficiency, and usage patterns, then uses scenario-based questioning to build a behavioral profile of each user's motivations, blindspots, and tradeoffs. This profile shapes every recommendation, ensuring they align with what actually drives each household to act. OwnWatt then delivers profile-matched recommendations that drive reliable action across bill reduction, device upgrades, and utility program participation, with a live decision log showing real-time optimization of every choice.
Target Audience
Primary customers are residential households seeking to reduce energy costs and coordinate their solar, battery, and EV investments, as well as utilities and OEMs needing reliable residential program participation and device adoption.
Features
- Household energy audit that ranks opportunities by impact, effort, and household fit across rate plans, peak-hour costs, and device inefficiencies
- Behavioral profiling engine built on scenario-based questions that reveal decision blindspots, motivations, and personal tradeoffs around comfort, cost, effort, and control
- Real-time decision log that automatically coordinates EV charging, battery dispatch, solar usage, and rate plan selection based on behavioral profile and live pricing
- No-hardware approach that works with existing devices and apps, eliminating installation barriers
- Prosumer activation engine that matches device upgrade recommendations to household readiness and drives participation in demand response, TOU enrollment, and virtual power plant programs