Coresignal vs OpenGTM

Coresignal provides real-time, multi-source public web data about companies, jobs, and professionals through APIs and flat-file datasets. It says its coverage spans 4.5 billion records from more than 15 sources. Dataset formats include JSON, JSONL, CSV, and Parquet. Data is offered at Base, Clean, and Multi-source processing levels; the Multi-source option combines and enriches material from multiple public sources. Its API catalog includes company, employee, and jobs endpoints with search, collection, bulk collection, and enrichment functions where applicable. Listed integrations include MCP Server, n8n, Zapier, Clay, Databricks, Google Cloud, Amazon S3, Snowflake, and Azure. Coresignal identifies investment, sales technology, HR technology, and market research as customer areas. It says it collects publicly available business data, excludes private or sensitive data and login-secured areas, and aligns its privacy policy with CCPA and GDPR. The free tier gives 2,000 credits for a 7-day trial, issued once per company email domain. Paid plans start at $49 a month.

OpenGTM is an open-source, self-hosted workspace for go-to-market teams and their agents. It handles lead sourcing and enrichment, AI research with cited answers, buying-intent tracking and sending qualified records to other tools. Workbooks combine imports, formulas, HTTP columns, enrichment waterfalls, AI research and output columns, with estimated spend visible before runs. Teams can segment live audiences, monitor hiring and buying signals, and schedule refreshes and automations. Listed activation destinations include HubSpot, Salesforce, Slack, Sheets, Airtable, Instantly, Smartlead, webhooks, warehouses and consent-gated ad audiences. The workspace is also available through REST, webhooks and an auditable MCP server with scoped read and write access. The project says data remains on the user's infrastructure and external calls use provider keys selected by the user. Teams can set workbook budgets to stop paid calls at a ceiling, although provider charges may apply. The software is free under AGPL-3.0. Installation requires Git, Docker with Compose v2 and roughly 4 GB of RAM. The project is pre-1.0; public multi-tenant hosting needs further work beyond team-controlled Compose deployment.