SignalPilot for Data Scientists

Explore Data 10x Faster

SignalPilot understands your notebook context, writes Python/SQL, and iterates until you have the analysis you need. No more copy-pasting between tools.

Real Problems, Real Solutions

Spending hours on EDA before getting to insights

The Problem

Writing boilerplate pandas code, generating basic visualizations, and checking data quality manually

With SignalPilot

Ask SignalPilot: 'Explore this dataset and find interesting patterns.' It generates summary stats, distributions, correlations, and highlights anomalies.

Forgetting the analysis from last week

The Problem

Re-discovering insights because context is scattered across notebooks, Slack, and your brain

With SignalPilot

SignalPilot remembers your previous analyses. Ask 'What did I find about customer segments?' and it recalls your validated findings.

Stuck on complex pandas operations

The Problem

Googling window functions, groupby aggregations, and reshape operations repeatedly

With SignalPilot

Natural language: 'Calculate rolling 7-day average revenue per customer segment.' SignalPilot writes the pandas code and explains it.

Built for How You Work

SignalPilot integrates deeply with your existing tools and workflows.

Notebook-Native AI

SignalPilot lives in your notebook, not a separate chat window. It sees your variables, dataframes, and outputs. Ask about the df you just loaded—it knows the schema.

Agentic EDA

Point SignalPilot at a dataset and ask 'What's interesting here?' It explores distributions, correlations, outliers, and missing data patterns automatically.

Multi-Session Memory

Your validated business logic, data quirks, and successful analysis patterns are remembered. Future analyses benefit from past learnings.

Privacy Mode

Working with sensitive data? Enable privacy mode to keep all analysis local. Your data stays on your machine—only the AI reasoning is processed externally.

Common Use Cases

Exploratory data analysis

Customer segmentation

Cohort analysis

Correlation discovery

Data quality assessment

Visualization generation

Works With Your Stack

SignalPilot integrates with the tools you already use.

Pandas
NumPy
Matplotlib
Seaborn
Plotly
Scikit-learn
I used to spend 60% of my time on data wrangling. SignalPilot handles the tedious parts so I can focus on finding insights.
Senior Data Scientist, Enterprise

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