NotebookPipeline
Daily demand forecast on autopilot
Build the forecast once in a collaborative notebook, then schedule it as a pipeline so updated demand projections land in your control room every morning.
Talk to your grid data, build forecasting tools, deploy live dashboards and automate alerts — all from one platform connected to the meters, sensors and markets your team already relies on.
See how it worksAsk your meter readings, telemetry and demand data in plain language
From notebook to live app for demand, asset health and trading desks
Schedule demand forecasts, exception alerts and regulatory reports
From asking a question to shipping a live grid dashboard, MINEO covers the full journey — connected to the meters, sensors and market data your energy team already relies on.
Connect any datasource — meter readings, grid telemetry, demand forecasts, market prices — and start asking questions in natural language. Threads auto-generates SQL, runs code, and delivers answers with interactive charts and tables. Build custom AI assistants with the model of your choice.
Threads · Grid analysis { "tool": "slack-mcp", "action": "create_task", "summary": "Alert the grid ops team in Slack" }
via slack-mcp · just now
More than Jupyter. MINEO Notebooks combine code, AI assistant cells, interactive widgets and visual tools in one collaborative environment. Perfect for forecasters, grid analysts and asset engineers — write Python, explore your data, and deploy as live apps from the same notebook.
File View Block Kernel Help 
Compare load evolution across regions and substations.
df = mineo.query("SELECT region, SUM(load_mw) FROM meter_readings GROUP BY region")
px.line(df, x="hour", y="load_mw", title="Demand Forecast")
Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.
df.sort_values("revenue", ascending=False).head()
| Region | Revenue | Growth |
|---|---|---|
| North America | $1.8M | +12% |
| Europe | $1.1M | +8% |
| APAC | $820K | +23% |
| LATAM | $480K | -3% |
Turn notebooks into always-on dashboards and interactive applications for grid operations, demand forecasting, asset health and trading. Deploy with Streamlit, Gradio, Dash and 6+ more frameworks. Custom domains, white-label branding and embeddable visualizations — ready for your operators.
Mineo · Grid dashboard Last updated: 2 minutes ago
Peak load
4.2 GW
+6% vs Q3
Active meters
182,540
+2% vs Q3
Outage rate
0.8%
-4% vs Q3
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Acme Corp | NA | $245K | Active |
| TechFlow GmbH | EU | $182K | Active |
| Sakura Ltd | APAC | $156K | Pending |
| DataBr SA | LATAM | $98K | Active |
A complete Linux development environment accessible from your browser. Install any package, any tool — Claude Code, Codex, Gemini CLI. Build your forecasting models with the libraries you trust, connect to your grid datasources and collaborate with your team. No local setup required.
VS Code — Dev Environment Explorer
import streamlit as st
from mineo import DataSource
import plotly.express as px
st.set_page_config(layout="wide")
st.title("Grid Dashboard")
ds = DataSource("grid_db")
df = ds.query("SELECT * FROM meter_readings")
# Layout
col1, col2 = st.columns(2)
col1.metric("Peak load", f"{df.load_mw.max():,.1f} MW")
col2.metric("Meters", f"{df.meter_id.nunique():,}")
# Charts
fig = px.line(df, x="hour", y="load_mw", color="region")
st.plotly_chart(fig, use_container_width=True)
mineo-dev@workspace:~/project$
Successfully installed plotly-5.22 scikit-learn-1.5
Your app is live at https://grid-dashboard.mineo.app
✓ Deployed successfully
Chain notebooks into production workflows. Schedule recurring runs with cron, trigger via REST API, and monitor execution in real time. From daily demand forecasts to exception alerts — build reliable workflows without infrastructure overhead.
/ Projects / grid / Daily demand forecast Elements
Resource Config
Scheduling
API
The biggest unlocks come when MINEO's building blocks share the same logic — the same notebook becomes a daily pipeline, a live grid dashboard, or an answer in a Threads conversation.
Build the forecast once in a collaborative notebook, then schedule it as a pipeline so updated demand projections land in your control room every morning.
Analysts query meter and telemetry data conversationally with Threads while operators get the same numbers in an always-on Live App dashboard.
Prototype the model in a Cloud Dev Environment, refine it in a notebook with the team, and ship it as an asset-health Live App without rewriting.
Use MINEO to talk to your grid data, build forecasting tools, deploy live dashboards and automate alerts — all from the same workspace.