Landbase, the GTM infrastructure company for the agentic era, today announced the launch of GTM-3 Omni, its next-generation model for agentic go-to-market discovery, qualification and outreach, and published the benchmark results behind it.

Where GTM-2 unified natural language targeting with omnichannel campaign strategy, GTM-3 answers a harder question: can an agent reason over business data better than a human working a filter-and-keyword tool? Landbase’s AI Lab built a benchmark to settle it.

Four vendors (Landbase, Clay, Apollo and ZoomInfo) were each given the same 26 list-building prompts, the same qualification criteria and the same judge. Every company and person each vendor returned was independently re-verified and scored against identical standards. The only variable was what each vendor returned.

Vendor

Precision

Most precise list (of 26 prompts)

Landbase (GTM-3 Omni)

76.7%

18

Clay

47.9%

4

Apollo

36.0%

1

ZoomInfo

23.2%

0

Landbase achieved 76.7% precision, compared with 47.9% for Clay, 36.0% for Apollo and 23.2% for ZoomInfo. Landbase won 18 of 26 prompts outright and delivered the highest first-page accept rate: 76.1% of the first 100 rows a buyer would actually work.

“Landbase was founded on the premise that you should no longer work for your software; your software should work for you,” said Daniel Saks, Co-Founder and CEO of Landbase. “We’ve now proven that AI can automate the work, from TAM mapping to list building to account research, so reps can do more of what they love: selling and cultivating human relationships.”

Precision Over Speed, by Design

GTM-3 Omni is not the fastest way to produce a list. A filter-based tool returns rows in seconds. GTM-3 takes roughly two minutes, because it plans the search, qualifies every candidate against the buyer’s actual criteria and discards what doesn’t hold up.

That trade is the product. A rep working a 77%-precise list of 1,000 companies has 767 real conversations available. The same rep on a 36%-precise list burns two out of every three touches on the wrong account and pays for the volume. Landbase customers have observed 2x or better campaign performance once list precision improves.

“With Landbase, agents can explore and reason over data to optimize go-to-market workflows with greater efficacy than humans. Landbase outperforms alternatives at identifying desired prospects by 2x in precision. When paired with targeted outreach, more precise audiences can drive 2x or greater improvement in campaign performance.”

Hua Gao, a Stanford Ph.D. and co-founder of EverString (acquired by ZoomInfo), leads Landbase’s Applied AI Lab.

What’s New in GTM-3 Omni

  • Reasoning over filtering: GTM-3 explores, plans, qualifies and scores every candidate against the buyer’s stated criteria in natural language, rather than mapping a prompt onto a fixed filter set.

  • Benchmarked precision: The first GTM model released alongside a reproducible, vendor-agnostic benchmark, with the same prompts, same criteria, same judge and a published methodology.

  • Native in the agentic CLI: GTM-3 runs directly inside Claude Code, Codex and Gemini CLI, where GTM and RevOps teams already work.

  • Enterprise and private equity deployments: Portfolio-wide GTM transformation across multiple operating companies, with Landbase’s forward-deployed data engineering team embedded alongside GTM leaders.

Availability

GTM-3 Omni is available today in the Landbase platform and natively in Claude Code, Codex, and Gemini CLI. Full benchmark methodology and per-prompt results are published here.

About Landbase

Landbase is GTM infrastructure for the agentic era. Its AI Lab develops domain-specific GTM models that let agents reason over business data to find, qualify and engage a company’s next customer, natively inside the agentic CLIs where teams already work. Founded in 2023 and headquartered in Mountain View, California, Landbase has raised over $42.5M from leading investors including Sound Ventures, Picus Capital, A*, Firstminute Capital and 8VC.

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