Overall Score
11
of AI companies
Create GPT assistants and Custom GPTs from your databases. 1. Set up your Data Source (database) 2. Add some Data Views (SQL scripts) 3. Co
Create GPT assistants and Custom GPTs from your databases. 1. Set up your Data Source (database) 2. Add some Data Views (SQL scripts) 3. Configure your GPT Assistant (from selected sources) 4. Chat with the built-in Assistant or create a custom GPT 5. Publish it on the ChatGPT store or share it pri...
Overall Score
11
of AI companies
Overall Score
11
GitHub Stars
—
Monthly Visits
964
Community Saves
489K
Create GPT assistants and Custom GPTs from your databases. 1. Set up your Data Source (database) 2. Add some Data Views (SQL scripts) 3. Configure your GPT Assistant (from selected sources) 4. Chat with the built-in Assistant or create a custom GPT 5. Publish it on the ChatGPT store or share it pri...
Latest detected signals across traffic, developer activity and community mentions.
Indexed by indexator.ai
Featured on Product Hunt
| Keyword | Volume / Mo | CPC |
|---|---|---|
| ngrok chat | 280 | — |
Create GPT assistants and Custom GPTs from your databases. 1. Set up your Data Source (database) 2. Add some Data Views (SQL scripts) 3. Configure your GPT Assistant (from selected sources) 4. Chat with the built-in Assistant or create a custom GPT 5. Publish it on the ChatGPT store or share it pri...
Get notified when score, traffic, GitHub or community signals change.
Latest detected signals across traffic, developer activity and community mentions.
Indexed by indexator.ai
Featured on Product Hunt
Six signals, each 0–100, blended into the overall by their listed weight.
Generated from public signals and search intent.
Each dimension is weighted (traffic 20% · community 25% · growth 15% · momentum 15% · innovation 10%) and combined into the overall.
| Keyword | Volume / Mo | CPC |
|---|---|---|
| ngrok chat | 280 | — |
489.1K
Rating
—
Views
—
Category
ChatGPT
Pros · 18
Cons · 10
Rating distribution
Release history · 1+
Initial release of DataLang.
Q&A · 21
Datalang is an AI tool that enables users to query their databases using natural language, effectively bridging the gap between technical expertise and end-users.
Datalang works by converting the questions posed by the users in natural language to database queries. It uses GPT-3 to generate natural language answers for the users based on their queries.
You can ask Datalang almost any question you would ask a data analyst. Examples include questions about the number of users in a given timeframe or the most common values in a specific field.
No, you don't need any technical knowledge to use Datalang. You just need to know your data source connection string.
Datalang ensures data security by encrypting connection string credentials. The credentials are only decrypted when necessary for data operations.
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