Energy Ocean

Helping you navigate the high and low tides of energy assets

EnergyOcean uses generative AI to predict electricity prices and optimize energy operations — helping businesses cut costs, home energy devices avoid peak pricing, and utilities run smarter grids.

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What We Do

Smarter energy decisions,
powered by generative AI

From predicting tomorrow's electricity prices to managing a fleet of distributed energy assets — EnergyOcean gives you the intelligence to act first.

Energy Price Forecasting

Know what electricity will cost before you buy or sell. Our GenAI models analyze historical market patterns and deliver accurate price predictions hours ahead, so you can plan with confidence.

Virtual Power Plant Management

Coordinate your solar panels, batteries, EVs, and flexible loads as a single smart asset — automatically optimized to maximize value and minimize costs.

Real-Time Market Signals

Stay ahead of market shifts. EnergyOcean continuously monitors live price data and grid conditions, surfacing opportunities to save money or generate revenue.

Simple API Integration

Connect in minutes with our developer-friendly REST API. No complex setup — just send your data and get actionable forecasts back instantly.

Core Technology

How our GenAI-Powered Forecasting Works

A transformer architecture adapted for time series — tokenizing energy data, predicting future patterns, and reconstructing actionable forecasts.

"valley""peak""climb"
Tokenization
Chunks time series data
Transformer
Transforms input sequence into another
Probability: 90%
"drop""peak""valley"
Statistics
Most likely token sequence
"drop""peak""valley"
De-tokenization
Re-samples tokens into time series data

Tokenization

Raw time series is segmented into meaningful chunks, each assigned a descriptive token like "valley", "peak", or "climb" that captures its shape and trend.

Transformer Model

A large-scale transformer — the same architecture behind modern LLMs — processes the token sequence and generates a probability distribution over future tokens.

Statistical Decoding

Sampling algorithms select the most probable continuation, such as "drop, peak, valley", and quantify forecast confidence with a probability score.

De-tokenization

Predicted tokens are reconstructed back into real-valued time series data — reproducing waveform shape, scale, and units as a usable forecast.

Get Started in Minutes

Three steps to your first AI forecast

01

Get Access

Request an API key and you're ready to go. Setup takes minutes, not days — no infrastructure required on your end.

02

Share Your Data

Send us your historical energy data via our simple API. We handle the GenAI — you just point us at your numbers.

03

Act on Forecasts

Receive clear predictions and confidence ranges in milliseconds. Use them to make smarter buying, selling, and dispatch decisions.

Our Team

Built by a domain expert

William A. Rodriguez Jimenez

William A. Rodriguez Jimenez

Founder & CEO

BSc & MEng in Artificial Intelligence, MIT

MSc in Energy Systems, Oxford

William studied intelligent EV charging during his MEng thesis at MIT. Then, at Oxford, William's dissertation focused on forecasting day ahead residential electricity prices in London using GenAI. William has worked at Tesla, Apple, Iberdrola, Morgan Stanley, and the United Nations as well as smaller startups.

linkedin.com/in/williamrj

Ready to Get Started?

Get API access and start building GenAI-powered energy forecasting into your products today.

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