DataLang
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 Assi...
Last verified:
What is DataLang?
DataLang is an AI-powered platform that lets users create custom GPT assistants and chatbots directly from their databases and data sources. Users connect databases like Postgres or MySQL, Google Sheets, Notion, files, websites, or text, then define data views using SQL scripts to expose specific information. They configure a GPT assistant selecting relevant sources, chat naturally in plain language to query data, and share the chatbot via public URL, website embed, ChatGPT Store, or API for team or customer access.
Key features include seamless data source integration without coding, natural language querying powered by GPT models, built-in assistant for instant insights, custom GPT creation and publishing, real-time data syncing options, and flexible sharing methods. It supports multiple database types (SQL Server, Snowflake), files, HTML, and more, making data accessible to non-technical users while allowing advanced SQL control for experts.
Designed for businesses, analysts, teams, and non-tech users needing quick data insights without complex queries. Ideal for sales teams querying branch data, customer support embedding chatbots, or enterprises building internal tools. It democratizes data access, boosts productivity, and enables AI-driven decisions from private data sources securely.
DataLang pricing
Pricing model: Freemium
Freemium model with Free plan (1 user, 1 data source, 100 credits, chatbot widget). Hobby: 2,000 questions/month, 1 data source, 1 user. Growth: 5,000 questions/month, 3 data sources, 3 users, API access. Enterprise: 10,000 questions/month, 10 data sources, 10 users, API access, priority support. Other sources mention Basic $19/mo, Pro $49/mo (6 users, 50 sources, 3k credits), Business $399/mo (12 users, 1000 sources, 20k credits); custom solutions available.
DataLang pros
- Connects Postgres, MySQL, Snowflake databases
- Integrates Google Sheets effortlessly
- Supports Notion pages as data sources
- Handles file uploads for custom chatbots
- Parses websites and HTML content
- Uses SQL for precise data views
- Creates custom GPTs from data
- Publishes to ChatGPT Store directly
- Embeds chatbots on websites
- Shares via public URLs easily
- API access for programmatic queries
- Real-time data syncing capability
- Natural language querying interface
- Built-in assistant for testing
- Multi-user support in plans
- Priority support for enterprises
- Self-hosting options available
DataLang cons
- Limited to 100 credits on free plan
- Only 1 data source in Hobby tier
- Single user per basic plan
- Questions capped at 2000/month Hobby
- No priority support in lower plans
- Requires SQL knowledge for views
- API only in Growth and above
- Credit-based usage limits
- No unlimited plan mentioned
- Setup needs data source config
Frequently asked questions about DataLang
How do I create a chatbot in DataLang?
Set up your data source like Postgres or Google Sheets, add data views with SQL scripts to define queryable data, configure GPT assistant from selected sources, chat with the built-in assistant to test, then share via URL, embed, GPT Store, or API.
What data sources does DataLang support?
Supports databases including Postgres, MySQL, SQL Server, Snowflake; tools like Google Sheets, Notion; plus files, text inputs, websites, and HTML for flexible chatbot creation from diverse data.
How can I share my DataLang chatbot?
Share via public URL for direct access, embed widget on your website, publish to ChatGPT Store for wider reach, or integrate via API for custom applications and programmatic use.
What is a data view in DataLang?
Data views are SQL scripts you add to expose specific datasets from your sources, allowing the GPT assistant to query precise information without exposing the entire database.
How do I open a DataLang account?
Visit datalang.io, click sign up or create account, enter name, email, contact details, set secure password, agree to terms and privacy policy, complete verification, then set up your first data source.
What are credits or questions in pricing?
Plans limit monthly questions or credits (e.g., Hobby 2000 questions, Free 100 credits), representing natural language queries processed against your data sources.
Can I sync data in real-time?
Yes, use sync options in API calls or settings to update the assistant's knowledge with fresh data from sources, keeping responses current.
Is self-hosting available?
Yes, larger organizations can opt for self-hosting solutions beyond cloud plans for more control over data and deployment.
What happens if I exceed plan limits?
Usage is capped per plan; upgrade to higher tiers like Growth or Enterprise for more questions, sources, users, and features to avoid limits.
How does authentication work for API?
API uses authentication via API key; generate key in settings, include in requests for secure access to your custom data endpoints and queries.