TamedTable, AI ETL in Natural Language
TamedTable is a source-available AI-first ETL tool that lets you load tabular data, issue natural-language commands to clean, enrich, classify, validate, and reshape data, and then replay or export those transformation recipes (browser and CLI).
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Quick Overview
Best for: Automation
What it does
Automation software for decision-makers comparing workflow fit and alternatives.
Best fit
Automation
Pricing snapshot
Free from $0.15 per 1,000 rows classified (benchmark result)
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TamedTable is an interactive, source-available AI ETL tool designed to let users talk to tabular data in natural language. It supports loading CSV, JSONL, Parquet, and Arrow files (local or via URL) and performs cleaning, enrichment, classification, validation, reshaping, and language processing by interpreting each row in context. The product runs in the browser and via a CLI, operates with your own API keys, shows changes as they happen, and records each transformation step so you can replay it on new data or export it as a Python script.
The interface emphasizes transparency and repeatability: every change is saved as a deterministic recipe that can be reviewed, undone, and replayed. It also offers a guided tour that replays real sessions for users who do not have an API key.
TamedTable is an AI ETL (Extract, Transform, Load) tool: load tabular data, describe what you want, and watch it transform. No formulas, no code. Source-available, runs on your own API key.
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Claim this listing for $29Key Features
Natural-language AI transformations
Issue commands in plain language (any supported human language) to clean, enrich, classify, validate, translate, summarize, and otherwise transform rows without writing formulas or code.
Context-aware row processing
The AI reads each row's context before deciding, enabling fixes like normalizing phone numbers, inferring country from city, and handling ambiguous dates appropriately by locale.
See changes and undo
See every change as it happens; history tracks steps so you can undo one change or all changes while the original file on disk is never touched.
Reusable recipes & automation
Every change becomes a saved step (a recipe) that can be replayed on new data or exported as a Python script.
Multiple file formats & loading options
Open CSV, JSONL, Parquet, and Arrow files from local disk, a URL, or bundled sample data.
Runs in browser and CLI
Use the open web app or command-line interface to run workflows and save outputs.
Lazy AI execution and previews
Preview AI transformations for low cost and run across all rows only when you commit; the UI shows rows, cost, and time estimates before running.
Export and interoperability
Save cleaned data to CSV/JSONL/Parquet/Arrow, save transformation flows (.flow), or export as Python (.py) to run outside TamedTable.
Source-available and runs on your API keys
The project is source-available and operates with your own API keys so models run against credentials you control.
Pricing
Guided tour available without an API key (replays real sessions). The project is source-available and can run with your own API keys.
Benchmark estimate
$0.15 per 1,000 rows classified (benchmark result)- Benchmark reported default model matched hand-checked labels 96.7% of the time
- Cost figure presented as part of benchmarking results, not a published plan
Use Cases
Data cleaning and normalization
Fix messy fields, normalize phone numbers and names, standardize country names, and correct capitalization and date formats using natural-language commands.
Enrichment and extraction
Extract structured data from free text, split addresses into components, infer missing values like country from city, and add inferred attributes such as industry from company names.
Classification and tagging
Label tickets, classify sentiment, sort titles by seniority, or bucket customers by inferred attributes using row-level model predictions.
Validation and anomaly detection
Flag suspicious emails, impossible dates, mismatched city/country pairs, or prices that appear incorrect prior to downstream use.
Language processing
Detect languages, translate comments to English, and summarize long text fields into one-line summaries.
Reshaping and joins
Perform deterministic operations like dedupe, joins (e.g., join on country codes), filters, pivots, and sorting to prepare data for analysis.
Integrations
Your API keys (model providers)
TamedTable runs on your own API keys so model calls use credentials you supply.
Export to Python
Export saved transformation flows as Python scripts to run pipelines outside the app.
CLI
Run TamedTable from the command line (the product supports both browser and CLI usage).
GitHub / source-available
The project is source-available and has a GitHub repository linked from the site.
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Step 1: Add API keys (only required the first time you start the app).
- 2 Step 2: Open a file (CSV, JSONL, Parquet, or Arrow) from local disk or by URL.
- 3 Step 3: Say what you want in natural language (supports multiple languages and voice commands).
- 4 Step 4: Watch the AI propose and apply changes; undo any change you dislike.
- 5 Step 5: Automate by saving the transformation recipe and replaying it on new data or exporting as Python.
Support
web app
Open the web app from the site to interact with TamedTable and try the guided tour.
GitHub
Source repository and issues are available via the project's GitHub links on the site.
guided tour
A guided tour replays real sessions for users without an API key.
API
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