Collect
Gather useful information from relevant sources and services.
DataBG builds structured data and machine-payable tools that make useful information easier for applications, developers and AI agents to discover and use.
Information is distributed across websites, databases, public registers, APIs and different formats.
Software and AI agents often need to discover sources, interpret inconsistent structures, normalize data and build one-off integrations before information becomes useful.
DataBG aims to provide a reusable machine-access layer between information sources and the systems that need them.
Gather useful information from relevant sources and services.
Normalize information into predictable formats that software can consume.
Make datasets and repeatable operations available through machine-readable APIs and tools.
DataBG started with Bulgarian structured data because it is a practical market in which to build and validate the platform.
The underlying architecture is intentionally broader: datasets can cover countries, companies, markets, organizations, locations, public information and other domains worldwide.
The long-term goal is a global catalog of machine-accessible data and utilities for the agentic web.
Discovery, schemas and access are designed for software and autonomous agents.
Datasets and tools can be combined into larger automated workflows.
x402 enables machine-to-machine payments for individual resources without a traditional checkout.