EveryCent gives low-income families the same grocery price forecasting that retailers use against them, so every dollar goes further.
EveryCent forecasts grocery prices using 25 years of real USDA retail price data and Google's TimesFM 2.0 AI model. It tells families whether to buy an essential item now or wait for a better price — turning complex forecasting into one simple decision.
Grocery stores use sophisticated price forecasting software to decide when to stock up on inventory. But the families who shop at those stores — especially the 40 million Americans on SNAP benefits — have no access to that same intelligence. They see today's price and have to guess whether it will go up or down next week.
We wanted to flip that dynamic. EveryCent gives low-income families the same price forecasting power that retailers already use, wrapped in an interface simple enough for anyone to use on their phone.
The egg price crisis of 2024-2025 made this feel urgent. Prices went from $2.99 to $6.23 per dozen in 12 months due to bird flu — a 108% increase that hit SNAP families hardest because eggs are one of the cheapest protein sources available. A tool that predicted that spike could have saved a family of four $50 or more over that period.
- 🟢 Buy Now / Wait / Stable — clear AI-powered recommendations for every item
- 📅 SNAP Cycle Alignment — enter your EBT reload date and get a personalized shopping plan
- 💬 Live Market Context — Claude Haiku explains why prices are moving using real-time web search
- 🛒 Smart Shopping List — optimal buy dates for each item based on TimesFM forecasts
- 📊 Price Intelligence — AI-generated insights from 25 years of real price data updated daily
| Layer | Technology |
|---|---|
| Frontend | React + TypeScript + Vite + Tailwind CSS |
| Charts | Recharts |
| Backend | Node.js + Express |
| Database | Google BigQuery |
| Forecasting | BigQuery ML AI.FORECAST with TimesFM 2.0 |
| AI Context | Anthropic Claude Haiku with web search |
| Data | USDA Economic Research Service |
| Data Processing | Python + Pandas |
- USDA Meat Price Spreads — monthly retail prices for beef, chicken, eggs, bacon, milk (2024–2026)
- USDA Historical Price Spreads — retail prices for bacon, beef, and chicken going back to 2000
- USDA Farm-to-Consumer Spreads — white bread (2000–2023) and potatoes (2008–2026)
- Daily web search — today's real prices fetched via Claude with web search
| Metric | TimesFM 2.0 | Moving Average Baseline |
|---|---|---|
| MAE | $0.06 | $0.14 |
| RMSE | $0.08 | $0.19 |
| R² | 0.91 | 0.76 |
- Node.js 18+
- Google Cloud account with BigQuery enabled
- Anthropic API key
git clone https://github.com/YOUR_REPO_URL
cd ecoprice
npm install
echo "VITE_ANTHROPIC_API_KEY=your_key_here" > .env
gcloud auth application-default login
gcloud config set project pricepulse-hackdavis
npm run dev:fullpython update_prices.pybq --project_id=pricepulse-hackdavis query --nouse_legacy_sql \
--destination_table=pricepulse.forecast_results --replace \
"SELECT * FROM AI.FORECAST(TABLE pricepulse.essential_prices, DATA_COL => 'price_usd', TIMESTAMP_COL => 'price_date', ID_COLS => ['item_name', 'category'], HORIZON => 14, MODEL => 'TimesFM 2.0', OUTPUT_HISTORICAL_TIME_SERIES => TRUE)"