Databar

Databar provides a data enrichment engine designed for GTM teams and agents, enabling users to find, enrich, research, and monitor companies or people across many data providers in one workspace. It supports workflows that span spreadsheets, APIs, and agent-based access, with a unified credit system for results. The platform emphasizes accessibility for teams while offering tools for builders and developers to extend its capabilities.

Databar presents a visual workflow environment called Flows, where users chain enrichments, AI steps, and conditional logic into pipelines. Pipelines can be tested on sample rows to preview costs before running on entire tables, and can be executed in multiple ways, including on tables, schedules, or via API. The system is designed to be usable across surfaces, from spreadsheets to endpoints for code and MCP-hosted agents.

Databar offers features such as waterfall enrichments that attempt many providers in sequence until a verified result is returned, with verification built into the run. It supports two-way CRM sync and the ability to push data to CRM and outreach tools. The platform includes an AI research agent, a Chrome extension, an MCP server, and API/CLI access, with integrations to over 160 data providers.

Databar provides multiple pricing plans and integrations, with credits that are consumed only when a verified result is produced. The product emphasizes accessibility for teams while also offering a full feature set for builders, including a Python SDK, a CLI, and MCP for AI agent integration. It states plans include thousands of data providers and flexible usage options across surfaces and integrations.

Use cases

• Enrich CRM records and monitor signals for GTM teams
• Research and target accounts with 160+ providers
• Build scalable enrichment pipelines for teams