Conversational Data Analysis

Ask your data anything with Threads

Connect any datasource 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.

Natural language queries with auto-generated SQL
Custom Assistants with any AI model (OpenAI, Anthropic, Google)
Connect datasources, MCP servers, and web search
Code interpreter for advanced analysis and visualizations

"MINEO has the features of Power BI and Google Colab, all in one. I have been able to perfectly carry out both data analysis and visualization projects."

Juan Pedro P. • Data Scientist, MIOTI

Explore Threads

Threads — Sales Analysis

sales_dbmarketing.csv

Ask anything about your data...

"MINEO has the features of Power BI and Google Colab, all in one. I have been able to perfectly carry out both data analysis and visualization projects."

Juan Pedro P. • Data Scientist, MIOTI

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AI-Powered Python Notebooks

Powerful Notebooks for data teams

More than Jupyter. MINEO Notebooks combine code, AI assistant cells, interactive widgets and visual tools in one collaborative environment. Write Python, drag-and-drop widgets, and deploy as Data Apps — all from the same notebook.

5 cell types: Code, Markdown, AI Assistant, Widgets, Snippets
10+ no-code widgets: SQL Query, Chart, KPI, Table, Form, Image, Upload and more
Real-time collaboration with multiple users
AI wand for code suggestions and explanations per cell
One-click deployment as Data Apps

"It is super powerful. You can create all the BI you need using Python directly as if it were a Jupyter Notebook but with a much better presentation."

Martin G. • Tech Lead, Data Truth

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File View Block Kernel Help

Revenue Analysis

100%

Code Markdown Assistant Widget Snippet

Revenue Analysis — Q4 2025

Quarterly breakdown by region with growth projections.

Region: All Regions

Results:

8

Apply

[1]

df = mineo.query("SELECT region, SUM(revenue) FROM sales GROUP BY region")

px.bar(df, x="region", y="revenue", title="Q4 Revenue")

NA

EU

APAC

LATAM

Assistant

Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.

[2]

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%

v12 ProWorker 2 CPU · 6GB

Deploy as App

"It is super powerful. You can create all the BI you need using Python directly as if it were a Jupyter Notebook but with a much better presentation."

Martin G. • Tech Lead, Data Truth

Explore Notebooks

Interactive Data Apps

Deploy Data Apps your team will actually use

Turn notebooks into Data Apps — always-on dashboards and interactive applications. Deploy with Streamlit, Gradio, Dash, and 6+ more frameworks. Custom domains, white-label branding, and embeddable visualizations — ready for your audience.

9+ Python frameworks: Streamlit, Gradio, Dash, Panel, and more
Always-on Data Apps with custom domains and 99.9% SLA
White-label branding and embeddable visualizations
Real-time data from connected datasources

"Great platform to build dashboards and data apps over Python Notebooks. MINEO Assistant is a truly game changer!"

Miguel G. • CTO, Perif.ai

See the Showcase

Sales Dashboard — Live App

Live

Sales Performance Dashboard

Last updated: 2 minutes ago

Filters Region: EMEA Export

Total Revenue

$3.9M

+18% vs Q3

Customers

1,692

+12% vs Q3

Avg Deal Size

$2.1K

-3% vs Q3

Monthly Revenue Trend FY 2025

$850K

Q1

$920K

Q2

$1.1M

Q3

$1.3M

Q4

Customer	Region	Revenue	Status
Acme Corp	NA	$245K	Active
TechFlow GmbH	EU	$182K	Active
Sakura Ltd	APAC	$156K	Pending
DataBr SA	LATAM	$98K	Active

myapp.mineo.app Powered by Streamlit

"Great platform to build dashboards and data apps over Python Notebooks. MINEO Assistant is a truly game changer!"

Miguel G. • CTO, Perif.ai

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Cloud Dev Environments

Full VS Code in the cloud

A complete Linux development environment accessible from your browser. Install any package, any tool — Claude Code, Codex, Gemini CLI. Deploy with any Python framework, connect to your datasources, and collaborate with your team. No local setup required.

Full VS Code with extensions and terminal
Install any tool: Claude Code, Codex, Gemini CLI
Custom Docker images and GPU acceleration
Connected to MINEO datasources and Git integration

"Excellent platform combining Google Colab with great data visualization and analytics."

Manuel M. • Senior Deep Learning Scientist

Start Building

VS Code — Dev Environment

Python 3.11 4 CPU • 8GB

app.py

pipeline.py

import streamlit as st

from mineo import DataSource

import plotly.express as px

st.set_page_config(layout="wide")

st.title("Sales Dashboard")

ds = DataSource("sales_db")

df = ds.query("SELECT * FROM orders")

# Layout

col1, col2 = st.columns(2)

col1.metric("Revenue", f"${df.total.sum():,.0f}")

col2.metric("Customers", f"${df.customer_id.nunique():,}")

# Charts

fig = px.bar(df, x="month", y="total", color="region")

st.plotly_chart(fig, use_container_width=True)

st.dataframe(df.head(10), use_container_width=True)

TERMINAL | zsh

mineo-dev@workspace:~/project$

Successfully installed plotly-5.22 scikit-learn-1.5

Your app is live at https://sales-dashboard.mineo.app

✓ Deployed successfully

"Excellent platform combining Google Colab with great data visualization and analytics."

Manuel M. • Senior Deep Learning Scientist

Start Building

Automated Pipelines

Automate your data workflows with Pipelines

Chain notebooks into production workflows. Schedule runs with cron, trigger via REST API, and monitor execution in real time. From ETL to ML training — build reliable data pipelines without infrastructure overhead.

Chain notebooks as sequential pipeline steps
Schedule with cron or trigger via REST API
Configurable compute resources per pipeline
Execution history with logs and error tracking

"Easy interface to create a dashboard with Python code. The distribution of modules is seamless, without the limitations of libraries like Dash."

Henar M. • Biomedical Research Engineer

Learn about Pipelines

/ Projects / Finance / Daily Sales Pipeline

General Elements 3 Executions API

Elements

1 extract_sales_data.ipynb

2 transform_and_clean.ipynb

3 load_to_warehouse.ipynb

Resource Config

Worker Environment

ProWorker 2 cores · 6 GB

Scheduling

Crontab Expression 0 6 * * *

Every day at 06:00

Active

API

Enabled

POST /v1/pipelines/{id}/run

Last Execution Running • -- • Waiting

"Easy interface to create a dashboard with Python code. The distribution of modules is seamless, without the limitations of libraries like Dash."

Henar M. • Biomedical Research Engineer

Learn about Pipelines

The AI Data Platform for your whole team

Conversational Data Analysis

AI-Powered Jupyter Notebooks

Interactive Data Apps

Cloud Dev Environments

Automated Pipelines

Conversational Data Analysis

AI-Powered Jupyter Notebooks

Interactive Data Apps

Cloud Dev Environments

Automated Pipelines

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Ask your data anything with Threads

Powerful Notebooks for data teams

Deploy Data Apps your team will actually use

Full VS Code in the cloud

Automate your data workflows with Pipelines

What our customers think about MINEO

Martin G.

Ismael M.

Juan Pedro P.

Miguel G.

Manuel M.

Luis T.

Alejandro M.

Edgar M.

Henar M

Ready to Talk to Your Data?