ZoomInfo Launches the GTM.AI CLI and GTM Bench
ZoomInfo, a go-to-market platform provider, has released the GTM.AI CLI, a command-line client for its verified go-to-market data, and GTM Bench, a versioned benchmark that evaluates large language models and artificial intelligence agents on the work go-to-market teams actually do, like building target lists, enriching records, scoring accounts, and reaching decision-makers.
With ZoomInfo GTM.AI CLI, revenue teams can search and enrich companies and contacts; pull intent signals, Scoops, and news; and run agentic research directly from the shell. Every command reads the GTM Context Graph, which maintains identity-resolved data on more than 100 million companies, 500 million contacts, and billions of buying signals, continuously refreshed and continuously queryable. The GTM.AI CLI returns live, verified data on every call.
Installation is one command through Homebrew or npm, with prebuilt binaries for macOS, Linux, and Windows. Sign-in is OAuth in the browser, with no client ID or secret to paste. From there, the `gtm` command family covers company and contact search and enrichment, intent signals, Scoops, news, agentic account and contact research, and the customer's own GTM context. Results return as JSON, JSONL, CSV, YAML, or a table, so output pipes into warehouse jobs, CRM updates, and agent workflows. Coding agents can call the CLI directly, and the repository ships a skill for Claude Code.
The CLI connects to the same hosted endpoint as the ZoomInfo MCP server, sharing credentials and credit consumption, so teams already using ZoomInfo through Model Context Protocol add the terminal surface without a second integration. It joins the GTM.AI integrations already live across Claude, ChatGPT, Microsoft Copilot Studio, Salesforce Agentforce, HubSpot Breeze, Gong, LeanData, and Google Workspace. Governance travels with the data. Access control, permissioning, data lineage, AI policy, and audit logging apply to every CLI call, exactly as they apply to every other surface that consumes GTM.AI. Organizations keep one governance posture across the platform, the API, the MCP server, and the terminal.
Meanwhile, the GTM Bench Version 1 covers more than 20 jobs, four systems, and three models, and the methodology, sample tasks, and grading rubrics are published for scrutiny. Every GTM Bench result is graded against a senior GTM operator's work product on two independent axes. Answer measures which share of the requested work product the system delivers. Grounding measures which share of the returned data traces to a real, current source. A confident wrong answer scores negative. Rubrics are designed by GTM and RevOps practitioners, and competitors run at their best available configuration.
In the v1 run, ZoomInfo's GTM.AI led every pillar, with a GTM Bench Index of 77. It finished 98 percent of the operator's work product, returned 478 verifiable records per 1,000, and ran cheapest at $0.79 per task.
GTM Bench is a vendor-run benchmark, and ZoomInfo publishes it accordingly. The losses are shown plainly, including four categories where the ZoomInfo edge is thin or absent, from pure copywriting to owned CRM data no external tool can see. Grounding is graded against ZoomInfo's verified records, a reach measure rather than an independent audit. The benchmark is versioned, will be re-run on major model releases, and version 2 adds agentic multi-step workflows, international coverage, and an owned-data axis.
The system at the top is GTM.AI, ZoomInfo's headless GTM context layer. It exposes the GTM Context Graph (100M companies, 500 million contacts, billions of signals) and agentic orchestration through API and Model Context Protocol, with every record carrying a confidence score and its lineage. GTM.AI powers dozens of live integrations, including Salesforce Agentforce, HubSpot Breeze, Microsoft Copilot, Claude, ChatGPT, Gong, LeanData, and Google Workspace.