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Databar

Databar lets sales and growth teams find, enrich and monitor companies and people using 160+ data providers, AI research agents and waterfall lookups, from a spreadsheet, API or MCP server, with one credit balance.

Databar website screenshot
Image: framerusercontent.com

What is Databar?

Databar is a data enrichment and research platform for go-to-market teams. It connects more than 160 data providers, including well-known sources for firmographics, contacts, tech stacks and funding, and puts them behind one spreadsheet-style workspace and a single credit balance. Where no provider has the answer, an AI research agent reads the web and fills the gap.

The product is made by Databar, Inc. and is built for sales, revenue operations and growth teams, as well as agencies that build lead lists for clients. Developers can use the same tables through an API, SDK or MCP server, so AI agents can call Databar directly. Details are on the official Databar website.

Key Features of Databar

Search With Detailed Filters

You can search companies and people by size, growth, funding, investors, hiring by function and technologies mentioned in job posts. Previews are free, so you see the result count before spending credits.

Provider Network and Waterfalls

Enrichment columns pull from many providers. For emails and phone numbers, a waterfall tries one source after another until it finds a verified result. Requests that return nothing are not billed.

AI Web Researcher

For questions no database covers, such as a company's pricing model or main competitors, an AI agent browses the web and returns structured columns with sources you can check.

Signals and Monitoring

Databar can watch accounts for funding rounds, hiring surges, champion job changes and new tools, so your team can act when a prospect changes.

Workflows and Automations

Flows can branch on conditions, include AI steps and run on tables, on a schedule or when a signal fires. A typical flow researches a new sign-up, scores it and routes it to the right sequence.

CRM, API and MCP Access

Lists sync both ways with HubSpot, Pipedrive and Attio and can be pushed to Salesforce, Close and outreach tools. Tables are also available over REST, an SDK and CLI, and a hosted MCP server.

Databar Pricing

Databar uses credit-based subscriptions. Each workspace gets 100 free trial credits to start, and annual billing is advertised as saving 12%.

On monthly plans unused credits roll over for one month. Annual and quarterly plans receive their full allotment upfront.

Prices checked on October 27, 2026; check the official pricing page for current plans.

Databar Coupon Code

This partner code is listed for Databar:

  • FRIENDSOFDATABAR – 10% off.

To use a code, pick your plan on the official pricing page, continue to checkout and enter the code in the discount or promo code field before you pay. The reduced total should show before you confirm. Partner codes are set by the vendor and can be changed, paused or limited to certain plans at any time, so check the final amount at checkout.

Who Should Use Databar?

  • Sales and RevOps teams that keep CRM data complete and current
  • Growth teams building target account lists from funding or hiring signals
  • Agencies running lead generation and outbound for clients
  • Founders who want richer prospect data without buying several data tools
  • Developers giving AI agents enrichment and research tools through MCP

Is Databar Worth It?

If your team already pays for several data providers, Databar can cut costs and admin by putting them behind one account. The waterfall approach and no-charge misses also mean fewer wasted credits. The AI researcher is helpful for the custom data points that make outreach personal, and having the same tables available to code and agents is a plus for technical teams.

It is not a casual purchase. The cheapest plan is $99 a month, the free trial is small, and credit use varies with the providers you call, so expect to watch usage closely at first. Use the 100 trial credits to test match rates on your own data before committing.