DataLang

By translating natural language into precise database queries powered by GPT AI models, DataLang democratizes access to business data, removing the SQL knowledge barrier that typically restricts data access to technical employees and creates bottlenecks in data-driven decision-making.

The platform supports connections to a wide range of database types, allowing organizations to bring their existing data infrastructure into the natural language query environment without migration or data duplication.

Once a data source is connected, users interact with it conversationallyasking questions like 'What were our top 10 customers by revenue last quarter?' or 'How many users signed up in each country this week?'and receiving answers in natural language responses that communicate the insight rather than presenting raw query results that require further interpretation.

DataLang's chatbot builder capability allows organizations to create customer-facing or internal AI chatbots that are connected to their live databases, enabling automated responses to data-driven queries through conversational interfaces.

Support teams, sales teams, and customer portals can leverage these database-connected chatbots to provide real-time, data-accurate answers to common questions without requiring human agents to look up information manually or escalate to database administrators.

Security is a foundational design priority, with DataLang encrypting database connection strings and credentials and only decrypting them at the moment of a data operationensuring that sensitive connection details are never stored or transmitted in plaintext.

Organizations can connect multiple data sources to their DataLang environment and build multiple chatbots drawing from different databases, enabling a portfolio of specialized data assistants each scoped to the relevant data domain for their intended users.