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DataLang

DataLang

Chat with databases for intuitive data exploration.

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Introduction

Chat with your Databases

Key Features

Natural Language Processing

AI-Powered Insights

Data Analysis

Interactive Querying

Intuitive Data Exploration

AI

Frequently Asked Questions

What is DataLang?

Chat with your Databases

How to use DataLang?

Connect your data sources, set up data views with SQL, configure a GPT Assistant, create a Custom ChatGPT, and share it with users, employees, or customers.

Do I need any technical knowledge to use DataLang?

You need to know your connection string (e.g. postgres://{USER}:{PASSWORD}@{HOST}:{PORT}/{DATABASE}) and perform SQL queries. Once you have your data views set up, you can ask questions in natural language without needing any technical knowledge.

How does DataLang secure my data?

DataLang ensures data security through appropriate measures such as encryption and access control. It prioritizes the protection of user data.

What are some use cases for DataLang?

DataLang can be used for interactive querying, data analysis, creating custom GPT models for insights, and transforming data into API endpoints.

What types of questions can I ask in DataLang?

You can ask any natural language queries related to your database, such as retrieving specific data, analyzing trends, or obtaining insights.

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Use Cases

  • Exposing a specific set of data using SQL to train GPT and facilitate natural language conversations with the database
  • Seamlessly transforming database information into accessible and secure API endpoints
  • Having interactive conversations with the database using natural language queries
  • Creating tailored GPT models from the data for customized insights and interactions

How to Use

Connect your data sources, set up data views with SQL, configure a GPT Assistant, create a Custom ChatGPT, and share it with users, employees, or customers.
DataLang: Chat with databases for intuitive data exploration. | Review AI Tools