NotebookPipeline
Weekly trade reports on autopilot
Build the category and channel analysis once in a collaborative notebook, then schedule it as a pipeline so the weekly trade report lands in your team's inbox every Monday.
Talk to your commerce data, build internal tools, deploy live dashboards and automate recurring trade reports — all from one platform connected to the orders, customers and inventory your team already works with.
See how it worksAsk your orders, customers and inventory in plain language
From notebook to internal app for merchandising, category and ops
Schedule weekly trade reports, stock checks and data refreshes
From asking a question to shipping an internal app, MINEO covers the full journey — connected to the orders, customers and inventory your retail team already works with.
Connect any datasource — orders, customers, products, inventory, web sessions — 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 · Commerce analysis { "tool": "shopify-mcp", "action": "create_task", "summary": "Push a 10% discount on the bottom 20 SKUs" }
via shopify-mcp · just now
More than Jupyter. MINEO Notebooks combine code, AI assistant cells, interactive widgets and visual tools in one collaborative environment. Perfect for analysts, category managers and data scientists — write Python, explore orders and customers, and deploy as live apps from the same notebook.
File View Block Kernel Help 
Compare evolution across categories and channels.
df = mineo.query("SELECT category, SUM(revenue) FROM orders GROUP BY category")
px.bar(df, x="category", y="revenue", title="Weekly Revenue")
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 merchandising, category, growth and operations. Deploy with Streamlit, Gradio, Dash and 6+ more frameworks. Custom domains, white-label branding and embeddable visualizations — ready for your stakeholders.
Mineo · Commerce dashboard Last updated: 2 minutes ago
GMV
$2.4M
+22% vs Q3
Orders
18,430
+14% vs Q3
Avg basket
$78
-2% vs Q3
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Acme Corp | NA | $245K | Active |
| TechFlow GmbH | EU | $182K | Active |
| Sakura Ltd | APAC | $156K | Pending |
| DataBr SA | LATAM | $98K | Active |
A complete Linux development environment accessible from your browser. Install any package, any tool — Claude Code, Codex, Gemini CLI. Build your commerce models with the libraries you trust, connect to your datasources and collaborate with your team. No local setup required.
VS Code — Dev Environment Explorer
import streamlit as st
from mineo import DataSource
import plotly.express as px
st.set_page_config(layout="wide")
st.title("Commerce Dashboard")
ds = DataSource("commerce_db")
df = ds.query("SELECT * FROM orders")
# Layout
col1, col2 = st.columns(2)
col1.metric("GMV", f"${df.amount.sum():,.0f}")
col2.metric("Customers", f"{df.customer_id.nunique():,}")
# Charts
fig = px.bar(df, x="week", y="amount", color="category")
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://commerce-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 nightly order refreshes to weekly trade reports — build reliable workflows without infrastructure overhead.
/ Projects / commerce / Weekly trade refresh Elements
Resource Config
Scheduling
API
The biggest unlocks come when MINEO's building blocks share the same logic — the same notebook becomes a weekly pipeline, an internal dashboard, or an answer in a Threads conversation.
Build the category and channel analysis once in a collaborative notebook, then schedule it as a pipeline so the weekly trade report lands in your team's inbox every Monday.
Marketers explore customer cohorts conversationally with Threads while merchandising sees the same segments in an always-on Live App dashboard.
Prototype the recommendation model in a Cloud Dev Environment, refine it in a notebook with the team, and ship it as an internal Live App without rewriting.
Use MINEO to talk to your commerce data, build internal tools, deploy live dashboards and automate recurring trade reports — all from the same workspace.