DataOrangutan: Automate Spreadsheets by Example
DataOrangutan learns your spreadsheet workflows by comparing raw and processed examples, then automates repetitive data tasks for you going forward.
Overview
DataOrangutan takes the tedium out of spreadsheet cleanup by watching how you transform raw data into finished results. Simply feed it a before-and-after pair of spreadsheets, and the tool intelligently reverse-engineers the steps you took—whether that's reformatting columns, filtering rows, or restructuring data—so it can replicate that exact workflow on new files automatically.
Instead of manually recreating the same formulas, filters, and formatting every time a new batch of data comes in, users can rely on DataOrangutan to detect patterns and apply them consistently. This example-driven approach removes the need for scripting or complex macro-building, making sophisticated automation accessible to anyone who works with spreadsheets, regardless of their technical background.
Capabilities & Features
- Spreadsheet automation
- Workflow automation
- Data processing
- Machine learning
- Data analysis
Core Features
- Automated spreadsheet processing
- Workflow learning from before/after examples
- Pattern-based transformation detection
- Reusable automation for recurring data formats
Use Cases
- Automating repetitive data cleanup and formatting tasks
- Standardizing incoming data feeds into a consistent report format
- Reducing manual data entry corrections across large spreadsheet batches
- Speeding up recurring reporting cycles that follow the same transformation logic
Best For
- Data analysts
- Business analysts
- Spreadsheet users
- Data entry clerks
Pros
- •No coding or scripting required to build automations
- •Learns directly from real examples rather than rigid rule-setting
- •Saves significant time on repetitive spreadsheet tasks
- •Accessible to non-technical users
Cons
- •Accuracy depends on the quality and clarity of the example spreadsheets provided
- •May struggle with highly variable or inconsistent data formats
- •Limited transparency into exactly how the workflow logic is derived
- •Complex, multi-step transformations may require multiple example iterations to get right
How to Use
1. Gather a sample spreadsheet in its raw, unprocessed state. 2. Prepare the corresponding processed version showing the desired end result. 3. Upload both examples to DataOrangutan. 4. Let the system analyze the differences and learn the workflow. 5. Submit new unprocessed spreadsheets and let DataOrangutan automatically apply the learned transformations.
Frequently Asked Questions
Open in AI Studio
Ask our AI to evaluate if DataOrangutan fits your specific workflow.
Pricing
Pricing details are not currently published; prospective users should check directly with DataOrangutan for the latest plans and costs.
Pricing data is provided as a summary. Visit the vendor website for full tier details.