For RevOps leaders managing account assignment, Gradient Works is a territory-management platform that replaces static books with AI-scored dynamic account assignments and syncs lead-to-account matching and routing across Salesforce and HubSpot.
Presence & Market Position
Tracked · below panel floor — earned mentions are accruing toward the next scored window.
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Gradient Works positions itself as the territory planning platform for commercial sales, having recently broadened its homepage claim from a book-management pitch to full territory planning, built on AI account scoring measured against closed-won customers rather than static ICP rules, synced into Salesforce and HubSpot for RevOps teams running 10 to 100 reps. Public conversation about the product is early — a quieter footprint so far, with visibility concentrated around its own product announcements and messaging updates rather than a wider vendor debate.
Box, Gusto, Upwork, Attentive, ChurnZero, QuotaPath, Beekeeper, Thoropass, Omnipresent
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Business Profile
Gradient Works is a seed-stage company, founded in Austin in 2020 and running on a $2M seed round raised in 2021 alongside the release of its account-assignment product. The team has stayed lean at 21 people while building out from that single assignment tool into a fuller territory-planning suite (Market Map, Carve, and AI Researcher) sold into Salesforce and HubSpot shops. Customers span established software companies like Box and Upwork alongside growth-stage names such as QuotaPath and Attentive.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Gradient Works has shipped an API and an MCP server, giving connected agents such as Claude access to territory and account data directly. Inside the product itself, AI Researcher acts as an enrichment agent that turns plain-English prompts into structured account attributes, and Carve runs as a chat-based agent for modeling territory-planning scenarios — extending the same agent pattern from research into planning.
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