Upgrade from a co-pilot to a co-commander with your very own AI sidekick for pipelines, analytics, and machine learning.
Try our fully managed solution to access this advanced feature.
Mage Pro AI Sidekick is your intelligent assistant for data pipelines, analytics, and ML workflows. It helps you design, debug, and optimize your pipelines — faster and smarter — using natural language. Whether you’re building ETL processes, exploring data, or resolving code issues, Mage Pro AI understands your intent and delivers code, context, and insights on the spot.
Use it to:
It’s like having a senior data engineer available 24/7 — inside your repo.
Mage Pro AI is your always-on data expert. Whether you’re building data pipelines, designing warehouse schemas, troubleshooting integrations, or making sense of your analytics stack, Mage Pro AI has the answer. It’s trained to understand the language of modern data teams — from ETL to orchestration to compliance — so you can move faster, with confidence.
Just type your question — natural language is all it takes. Mage Pro AI instantly parses your query and provides accurate, actionable responses across a wide range of data topics: infrastructure, modeling, governance, ML, and more. It’s built into the Mage Pro platform and fine-tuned specifically for data engineers, analysts, and architects. No docs to dig through. No syntax to memorize. Just ask.
Data teams lose countless hours searching for answers across scattered documentation, Slack threads, and tribal knowledge. Mage Pro AI changes that. With expert-level responses at your fingertips, your team can solve problems faster, onboard more easily, and stay focused on high-impact work. It’s like having a senior engineer on call — 24/7.
Stop wasting hours piecing together pipelines by hand. Mage Pro AI can design and build complex data workflows in seconds. Just describe your goal in plain English, and Mage Pro AI auto-generates the full pipeline—every block, every dependency, every line of code.
Tell Mage Pro AI what you want to build—ingest from S3, transform with Polars, join with a Delta Lake table, run daily, alert on failure. Mage instantly maps out the entire pipeline and generates working code for each step, fully integrated with your existing tools and infrastructure.
Manually building pipelines is slow, error-prone, and often blocks teams from experimenting or scaling quickly. Mage Pro AI turns hours of setup into seconds of generation—so engineers can focus on what matters: logic, not boilerplate.
Design your pipeline one step at a time—without writing a single line of code. Mage Pro AI can generate complete, production-ready code blocks for every stage of your data workflow.
Tell Mage what you need:
“Load this CSV from S3,”
“Join with this Delta Lake table,”
“Clean nulls in this column,”
“Calculate weekly aggregates.”
Writing every block by hand is slow and repetitive. Mage Pro AI speeds up development by giving you smart, reusable code blocks that integrate cleanly with upstream and downstream steps.
Mage Pro AI helps you evolve your workflows by intelligently updating, refactoring, and improving code blocks in place.
Highlight a block. Ask Mage Pro AI to optimize it, update logic, or align with new requirements. The AI understands your pipeline context and rewrites the code accordingly.
Mage Pro AI handles updates safely, intelligently, and instantly—saving hours of debugging while ensuring consistency and performance across your pipeline.
Mage Pro AI helps you resolve issues in your pipeline code with intelligent, context-aware fixes.
Highlight the problematic block or describe the issue. Mage Pro AI analyzes the code and suggests a corrected version that works within the full pipeline context.
Debugging pipeline code wastes valuable time. Mage Pro AI reduces that friction by helping your team quickly find and fix issues.
Mage Pro AI makes it possible to build pipelines that detect failures, diagnose errors, and fix themselves.
When a pipeline breaks, Mage Pro AI iterates through debugging cycles, rewriting blocks and rerunning them until validation checks pass.
Mage Pro AI automatically fixes pipelines, ensuring that data quality checks are met without wasting hours chasing down errors.
With Mage Pro AI, you can ask questions about your pipeline data and get clear answers.
Ask Mage Pro AI questions like “Why did this block fail?” or “Are there outliers in this column?” It responds with insights, context, and suggested actions.
Mage Pro AI eliminates the need to query logs or write SQL—helping you understand your data instantly and take informed action.
Mage Pro AI transforms pipeline outputs into insightful, ready-to-use visualizations.
After a block runs, Mage Pro AI analyzes its output and auto-generates the most appropriate visualization—bar charts, line graphs, histograms, heatmaps, and more.
Visual feedback helps you debug faster and understand your data more deeply at every step—without needing to configure or write plotting code.
Mage Pro AI lets you turn raw pipeline outputs into smart, explorable tables—instantly.
Mage Pro AI creates interactive tables with sorting, filtering, and searching automatically after your pipeline runs—no front-end or dashboard setup needed.
Don’t stop at raw output. Instantly turn your data into interactive, insightful products for analysts, stakeholders, or pipelines.
Empower Mage Pro AI to give smarter, context-aware answers by enabling RAG (Retrieval-Augmented Generation).
When RAG is enabled, Mage Pro AI can reference your actual project files — including pipeline code, configurations, and documentation — to provide deeper, more accurate answers. This dramatically improves the AI’s ability to help with debugging, code generation, and pipeline understanding.
Without RAG, Mage Pro AI answers based solely on general knowledge and standard behaviors. With RAG enabled:
If RAG is not enabled, the AI will ask for permission before reading any of your files each time you make a request.
Create a file at the root of your project named ai_config.yaml
. This file defines which folders the AI is allowed to read and which files to exclude.
Create a file at the root of your project named ai_config.yaml
Once you’ve updated your ai_config.yaml
, call the following API to reindex your project files into the vector store:
After reindexing, Mage Pro AI will be able to answer questions using your real project data—enabling more personalized, precise assistance.
Create complete data pipelines from a single prompt. Describe your data goals in plain English and Mage Pro AI generates end-to-end ETL workflows with correct dependencies and block-level logic.
Use Mage Pro AI to generate data preparation, model training, and evaluation pipelines in seconds. Easily experiment and scale machine learning workflows without writing boilerplate code.
Need to load a CSV, clean nulls, or join with a Delta Lake table? Mage Pro AI generates clean, reusable code blocks tailored to your infrastructure, tools, and pipeline logic.
Highlight a broken step or describe the issue—Mage Pro AI suggests fixes, explains errors, and updates the code in context. Eliminate hours of debugging time.
Mage Pro AI can detect failed blocks, rerun them, and rewrite logic to meet validation rules—creating fault-tolerant pipelines that repair themselves automatically.
Want to understand why a block failed or check for anomalies? Mage Pro AI provides contextual answers and analysis—no SQL or log digging required.
Mage Pro AI analyzes pipeline outputs and automatically creates helpful visualizations and interactive tables—ready for review or sharing with stakeholders.
Test new data workflows, transform logic, or refactor pipelines in seconds using natural language. Mage Pro AI makes it easy to try new ideas without slowing down.