Clay vs OpenGTM

Clay is a spreadsheet-style platform for connecting information and automating work, aimed at salespeople, growth teams, and small agencies finding and reaching customers. It enriches data through more than 150 providers and can combine sources in multi-provider waterfalls. Claygent, its AI agent, can research the web and generate custom data points. Depending on the plan, users can track signals such as job changes, promotions, new hires, company news, social activity, and web intent. Integrations include Salesforce, HubSpot, Snowflake, and Google BigQuery. Clay can centralize audience data and sync ad audiences to LinkedIn, Meta, and Google. Its Salesforce integration can manage data, create or update records, and access reports and views. The Free plan allows up to 200 rows per table and excludes phone number enrichment. Actions measure platform usage; Data Credits cover data and AI from marketplace vendors. Clay says customer data is not used to train its AI models or those of its AI providers.

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.