The All-in-One AI Plugin for Data Scientists

Skills for data scientists 17

• data preprocessing advisorWalks you through cleaning, imputation, scaling, and imbalance fixes, like turning a 40 percent missing column into a usable feature.
• feature engineering advisorSuggests new features and transformations, such as lag and rolling averages for weekly sales forecasting.
• algorithm development assistantCovers the research lifecycle from preprocessing to documentation, for example structuring a paper-ready model comparison.
• ml algorithm selection assistantRecommends and compares models for your data, like choosing gradient boosting over logistic regression for tabular churn.
• big data analysis guideGuides large-scale workflows including anomaly detection and NLP, such as clustering millions of support tickets.
• model evaluation analystRuns full model evaluation with bias audits and robustness probes, for example testing a credit model across demographic groups.

Plus a start-here assistant, the prompt library and the app builder, and for members the daily brief.

Ready-made prompts 244

• Deep Learning in Image Analysis25 prompts, like Image Classification Assistant
• AI Model Evaluation20 prompts, like Active Learning Integration
• Data Preprocessing Techniques14 prompts, like Outlier Detection Methods Guide
• Feature Engineering and Selection17 prompts, like Categorical Variable Encoding Guidance
• Neural Network Architecture Design17 prompts, like Apply Regularization to Prevent Overfitting
• AI Ethics and Responsible AI10 prompts, like AI Bias Detection
• Machine Learning Algorithm Selection13 prompts, like Algorithm Complexity and Suitability Analysis

Apps you can build with AI 8

• Evidence-backed notebook analysis and reporting workspaceReduce notebook rework while preserving the analyst's reasoning. Demo included.
• Managed model training and deployment workspaceRuns training and deployment in one place, cutting handoffs between notebooks and production. Demo included.
• AI model test and monitoring workbenchTests models before release and keeps a defensible record, useful for regulated or high-stakes deployments. Demo included.
• Private fine-tuning and workflow automation workspaceFine-tunes models on your own data while keeping weights and data in-house. Demo included.
• AI model and agent performance operations workbenchShortens the loop from detected model failure to reviewed fix, useful for live prediction services. Demo included.
• Model comparison and selection workspaceProduces a documented model comparison, so selection decisions are reviewable instead of verbal. Demo included.
• Source-linked multi-model text and code workbenchConsolidates generation, coding, and analysis with source-linked outputs for audit. Demo included.
• Multi-model comparison and clarification workspaceCompares models on cost and quality in one owned workspace, useful when picking a vendor. Demo included.

AI agents 12

In the download. An agent runs a whole recurring task for you, step by step, and asks you before anything important. Ask your AI: "Run the Research Data Intake Validation Agent". Each one also has a guided set-up with sample data on its page.

• Research Data Intake Validation AgentA validated, reproducible working dataset with raw data untouched.
• AI Model Risk Register AgentA current register of live models with owners, reviews and risk status
• A/B Test Validity Check AgentA test result read only when the data is valid, with a clear recommendation
• Forecast Backtest and Refresh AgentForecasts that improve over time because every method is tested on the same history
• Model Fairness Audit AgentA documented review of how a model performs across groups, with tested mitigations and tradeoffs
• Baseline Versus Complex Model AgentThe simplest model that does the job, with evidence that added complexity was worth it
• Label Quality Audit AgentFind and fix the label errors that hold model quality down, and prove the fix with a retrained comparison
• Data Leakage Detection AgentRemove leaks from splits and features and produce an honest performance estimate
• Champion-Challenger Rollout AgentMove a replacement model from shadow to full traffic only while the evidence supports each step
• Decision Threshold Tuning AgentSet decision thresholds that minimize real-world cost and stay stable as data shifts
• Inference Cost and Latency Review AgentCut serving cost and tail latency without lowering model quality
• Model Selection Bake-Off AgentChoose a model with evidence on quality, cost and speed for the real task

Connections (MCP servers) 12

A guide in the download. A connection lets your AI work in an app you already use. You add only the ones you use: ask your AI "Which apps can you connect to?" and follow the steps on each connection's page.

• Jupyter Notebook MCP serverLet your AI write and run code inside your Jupyter Notebook, cell by cell, and read the results.
• Jupyter MCP serverLet your AI open, edit and run Jupyter notebooks for you while you watch. No install needed.
• MLflow MCP serverLets your AI look up MLflow experiments, runs, models, and traces and summarize them for you.
• Optuna MCP serverLet your AI run optimization experiments and show you the results as charts. Official.
• Google Colab MCP serverLet your AI open a Google Colab notebook, add and run code cells, and pick a GPU for you.
• Jungle Grid MCP serverLets your AI estimate, run and check GPU jobs on Jungle Grid, then fetch the results. Official. No install needed.
• pcq MCP serverLets your AI run, check and compare machine learning experiments in your project and report back what happened.
• Papers with Code MCP serverLets your AI search research papers and find the code, datasets, and results linked to them.
• Tech Trend MCP serverYour AI can gather fresh research papers, trending code, and FDA device news, then write you a short newspaper-style briefing.
• arXiv MCP serverLets your AI search arXiv for research papers and pull up their details and full text. No install needed.
• BigQuery MCP serverLets your AI look at your BigQuery tables and run SQL queries for you.
• Label Studio MCP serverLet your AI create and manage Label Studio projects, tasks, and predictions for you. Official.

Your Grok Bot team 12

• Data ScientistAnalyzes data, builds models, and delivers actionable business insights from complex datasets.
• Statistical AnalysisRuns statistical tests and reports results in APA format for academic research.
• Scikit LearnBuild and evaluate classical ML models with scikit-learn pipelines.
• Machine Learning Ops Ml PipelineOrchestrate a multi-agent MLOps pipeline from data ingestion to production serving.
• Senior Data ScientistDesign experiments, build predictive models, and perform causal analysis from your data.
• ShapExplains machine learning model predictions using SHAP values and visualizations.
• StatsmodelsFits and diagnoses statistical models for rigorous inference and forecasting.
• Ab Test SetupPlan statistically valid A/B tests with locked hypothesis, sample size, and pre-launch checklist.
• Ab TestingDesign statistically valid A/B tests and growth experiments.
• SeabornGenerate publication-quality Seaborn statistical plots from DataFrames with code only.
• Data AnalystAnalyzes numerical data to find trends, compare metrics, and produce statistical insights.
• Research AnalystConducts comprehensive multi-source research and synthesizes findings into actionable reports with trend analysis.