Landbase Launched GTM-3 Omni for Market Prospecting
The new model utilizes agentic planning to improve lead identification precision over established industry platforms.
Updated on Sept. 29, 2026 in Artificial Intelligence
Live Poll
Do you trust AI agents to perform complex business research accurately?
Landbase has officially released GTM-3 Omni, a market discovery tool that employs autonomous search planning to identify sales leads. The release follows benchmark testing where the model outperformed several incumbent lead-generation systems in precision.
Why it matters
The model aims to replace rigid, filter-based list generation with an iterative, goal-oriented approach to prospect identification. This shift towards agentic search aims to reduce the time and manual refinement required to build high-accuracy sales lists.
In a 26-prompt benchmark, Landbase GTM-3 Omni achieved 76.7% precision compared to lower scores from three competitors. The tool generates prospect lists in approximately two minutes, significantly faster than traditional manual curation methods.
The players
Landbase
A Mountain View-based firm that has raised over $42.5 million to develop autonomous market research and sales outreach infrastructure.
The details
GTM-3 Omni operates by planning searches and qualifying candidates against user criteria, moving away from the static, fixed-filter architecture common in legacy databases. By dynamically refining the search process, the model isolates relevant contacts more accurately than systems relying on broad boolean queries. This process allows the system to autonomously navigate candidate data rather than simply retrieving matches from a predefined list.
Timeline
Landbase was founded in 2023.
The GTM-3 Omni model was launched on September 29, 2026.
The Tech Race
Landbase is attempting to disrupt the established market for sales intelligence by replacing traditional filter-based retrieval with generative agentic workflows. This challenges the current dominance of incumbents like ZoomInfo and Apollo, which rely on large-scale indexing rather than active, prompt-based reasoning.
Users can now leverage the GTM-3 Omni model to generate prospect lists in roughly two minutes by providing descriptive prompts. This capability replaces manual filter-based workflows, though initial integration depends on current availability within the Landbase platform.
The takeaway
The performance gap demonstrated in the initial benchmark suggests a shift toward models that prioritize search reasoning over data volume. Future updates to watch include independent verification of these precision scores and the platform's long-term performance across varied enterprise use cases.
Further reading
For more on how new models are changing software automation, visit Artificial Intelligence.
Live Poll
Do you trust AI agents to perform complex business research accurately?
