PandasAI

What is PandasAI?

PandasAI lets people ask questions about their data in natural language. It began as an open source Python library, released under the MIT license, that turns questions into Python and SQL code, runs it against dataframes and databases, and returns answers, charts, cleaned data or generated features. The vendor also offers Annie, a hosted AI data analyst that connects to a company's databases and tools and answers business questions without SQL. The library supports multi-turn agents with follow-up questions and an optional Docker sandbox for safer code execution, and it can read CSV and Excel files plus PostgreSQL, MySQL, CockroachDB and Microsoft SQL Server. Cloud connectors for Snowflake, Databricks, BigQuery and Oracle, plus vector-store training, need an Enterprise license. Hosted plans are Plus at 29.99 euros per month and Pro at 99.99 euros per month, with Enterprise from $1,000+ per month.

Use cases

• Query CSV and Excel data in plain English
• Build charts from a question
• Clean datasets with missing values
• Ask follow-up questions in a chat agent
• Connect SQL databases to a chat interface
• Create business dashboards without SQL

Who it's for

• Data analysts
• Data scientists
• Business teams
• Python developers

Why use PandasAI

• Get answers without writing SQL or Python.
• Use the MIT-licensed library for free, or the hosted analyst when you want a managed product.
• Run generated code in a Docker sandbox when working with untrusted data.
• Enterprise options include on-premise and private VPC deployment.

PandasAI features

• Natural language questions translated to Python and SQL
• Charts and data visualization
• Data cleansing and feature generation
• Multi-turn agent with follow-up questions
• Docker sandbox for isolated code execution
• Semantic layer to describe tables and columns
• Connectors for CSV, Excel, PostgreSQL and MySQL
• Enterprise connectors for Snowflake, Databricks, BigQuery and Oracle
• SSO, role-based access and audit logs on Enterprise

PandasAI integrations

• PostgreSQL
• MySQL
• CockroachDB
• Microsoft SQL Server
• Snowflake
• Databricks
• BigQuery
• Oracle
• ChromaDB
• Qdrant
• Pinecone

How to get started with PandasAI

1. Install the library with pip or poetry, or start a free trial of the hosted analyst.
2. Load a CSV or Excel file, or connect a supported database.
3. Describe tables and columns in the semantic layer so questions map to the right fields.
4. Ask a question; PandasAI generates and runs Python or SQL and returns the result or a chart.
5. Use an agent for follow-up questions and share results as reports.

PandasAI limitations

• Snowflake, Databricks, BigQuery and Oracle connectors need an Enterprise license
• Vector-store training needs an Enterprise license
• Hosted plans are metered in monthly credits
• Many SaaS connectors on the hosted product are labeled as coming soon

PandasAI pricing

Yes, PandasAI has a free plan. Paid plans start at €29.99 per month, according to the official pricing page on 24 Oct 2026.

PandasAI plans

• Plus

  €29.99/mo

  • 100 credits per month
  • AI questions and data analytics
  • SQL databases (PostgreSQL, MySQL)
  • Premium support

• Pro

  €99.99/mo

  • 500 credits per month
  • AI questions and data analytics
  • Data lakes (BigQuery, Databricks, Snowflake)
  • Premium support

• Enterprise

  From $1,000+/month

  • SSO and SAML
  • Role-based access control
  • On-premise or private VPC hosting
  • Custom LLM integration

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

PandasAI alternatives

The main PandasAI alternatives listed on Debuly are Julius AI, Vanna, AI for Database, Firemetrics, HEAVY.AI and Gradio. The table compares pricing and platforms; order is A–Z.

1. 

   AI for Database

   Ask your PostgreSQL, MySQL or Google Sheets data questions in plain English and get charts, dashboards and automated alerts.

   Developer platformsProductivityAutomation and agents
   FreemiumVisit AI for Database (official site)
2. 

   Firemetrics

   FHIR-native clinical data repository for hospitals with SQL access, an MCP server and a local AI assistant.

   Developer platformsResearch and search
   Contact salesVisit Firemetrics (official site)
3. 

   Gradio

   Open source Python library for turning machine learning models into web apps and demos that you can share by link.

   Developer platformsCodingChat assistants
   Open sourceVisit Gradio (official site)
4. HA

   HEAVY.AI

   GPU-accelerated analytics database and visual analytics platform for large geospatial and time data, with natural-language queries.

   Developer platformsResearch and search
   FreemiumVisit HEAVY.AI (official site)
5. 

   Julius AI

   AI workspace for analysing data, researching, and building presentations, reports, websites, images and video from plain-language prompts.

   Research and searchProductivityDesign
   FreemiumVisit Julius AI (official site)
6. 

   Vanna

   Open-source Python framework for building user-aware AI agents, such as SQL data analysts, with an optional managed cloud.

   Developer platformsCodingAutomation and agents
   Open sourceVisit Vanna (official site)

PandasAI FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from pandas-ai.com · fetched 24 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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