Build intelligent data tools from CSV analyzers to full analytics platforms. Master AI-powered visualization, predictive modeling, NL querying, and real-time analytics.
Build a tool that lets users upload CSV files and get instant AI-generated summaries, column statistics, and data quality reports. The AI identifies data types, missing values, outliers, and suggests cleaning steps.
Create a tool where users describe the chart they want in natural language and the AI generates the appropriate visualization. Support bar, line, pie, scatter, and area charts with automatic axis labeling and color theming.
Build an AI-powered data cleaning tool that detects inconsistencies, duplicates, formatting issues, and missing values in tabular data. The AI suggests corrections and lets users approve or reject each change in a review interface.
Create a tool that ingests survey response data (CSV or Google Forms export) and uses AI to identify key themes, sentiment patterns, and demographic breakdowns. Generate executive summary reports with visualizations.
Build a real-time sentiment analysis dashboard that monitors text data from uploaded reviews, tweets, or feedback. Display sentiment trends over time, word clouds, and AI-generated insights about what drives positive or negative sentiment.
Create an interactive spreadsheet interface with an AI copilot sidebar. Users can ask questions about their data, request formula suggestions, and get step-by-step explanations of calculations — all in natural language.
Build a tool that transforms raw datasets into compelling data stories. Users upload data and the AI generates a narrative with embedded charts, callout statistics, and a scrollytelling presentation mode.
Create an educational tool that computes statistical measures on user-provided data and uses AI to explain each result in plain language. Cover descriptive stats, distributions, hypothesis tests, and correlations with visual aids.
Build a tool that analyzes time-series data to detect trends, seasonality, and change points. The AI explains each detected pattern in context and predicts where the trend is heading with confidence intervals.
Create an AI-assisted tool that converts data between formats (CSV, JSON, XML, YAML, SQL, Parquet schema). The AI infers schema, handles nested structures, and suggests optimal target formats based on the data shape.
Build a drag-and-drop business intelligence dashboard where users connect data sources and create widgets (charts, KPIs, tables). AI suggests relevant metrics, optimal visualizations, and auto-generates dashboard layouts from data descriptions.
Create a no-code predictive analytics tool where users upload historical data, select target variables, and the AI builds regression or classification models. Display predictions, feature importance, and model accuracy metrics with clear explanations.
Build a monitoring tool that continuously analyzes data streams for anomalies using statistical methods and AI. Display alerts with severity levels, root cause analysis, and suggested actions for each detected anomaly.
Create an AI-powered customer segmentation tool that clusters customers based on behavioral and demographic data. Visualize segments with interactive scatter plots and radar charts, and generate AI-written persona descriptions for each segment.
Build an A/B test analysis platform that computes statistical significance, effect sizes, and confidence intervals for experiments. The AI interprets results, warns about common pitfalls (peeking, multiple comparisons), and recommends next steps.
Create a tool that translates natural language questions into SQL queries, executes them against a database, and displays results with AI-generated visualizations. Support query history, saved queries, and query explanation mode.
Build a visual node-based editor for constructing data transformation pipelines. Users drag and connect nodes for operations like filter, map, join, aggregate, and AI-enrichment. Preview data at each step and export the pipeline as code.
Create a tool that connects to data sources and automatically generates polished business reports. The AI writes executive summaries, highlights key metrics, flags concerns, and formats everything into a downloadable PDF with branded styling.
Build a no-code machine learning platform where users upload training data, configure models through a visual interface, and train classification or regression models. Include model evaluation dashboards, comparison views, and one-click deployment as an API endpoint.
Create a real-time analytics dashboard that ingests streaming data via WebSockets, computes running aggregations, and updates visualizations live. The AI detects noteworthy events in the stream and generates instant commentary on emerging patterns.
Build an interactive data warehouse exploration tool with schema visualization, AI-guided query building, and automated data profiling. Users can browse tables, understand relationships via ER diagrams, and ask questions that span multiple joined tables.
Create a comprehensive time series forecasting workbench that supports multiple algorithms (moving average, exponential smoothing, ARIMA-style, neural prophet). Users compare model accuracy, tune parameters visually, and the AI explains which model works best and why.
Build a data governance tool that catalogs datasets, tracks data lineage, enforces quality rules, and manages access policies. The AI auto-generates documentation, suggests classification tags, and detects PII across datasets automatically.
Build a complete, end-to-end analytics platform that combines data ingestion, transformation, warehousing, AI-powered analysis, and interactive dashboarding. Support multiple data sources, scheduled pipeline runs, collaborative workspaces, and natural language exploration across all connected data.
Create a browser-based data science IDE with a notebook interface, integrated AI copilot, visual data exploration, and reproducible experiment tracking. Support Python-like data operations via a JavaScript DSL, GPU-accelerated model training, and one-click deployment of models as REST APIs.