SalesIntel is a pipeline generation platform for GTM teams.

Intent data shows that an account is already evaluating a category, usually through topic surges or website behavior. Predictive signals show that an account is about to enter a buying cycle, through events like funding rounds, leadership changes, hiring surges, or new technology adoption. Intent data tells you to move now. Predictive signals give you weeks or months of lead time.

SalesIntel guarantees 95% accuracy on AI+Human-verified contacts and refreshes records on a 90-day cycle. Records are built by merging public, partner, and proprietary sources, then verified by a team of more than 2,000 researchers. Research On Demand covers any contact or account not already in the database.

An ICP fit score is a quantified measure of how closely an account resembles the customers a company already wins. SalesIntel’s ICPIntel builds the score by analyzing closed-won accounts across multiple dimensions including revenue, geography, headcount, departments, industry, technology stack, and keywords. It returns a dimension-by-dimension breakdown rather than a single opaque number.

A buying committee is the group of people inside an account who must agree before a B2B purchase closes, typically an economic buyer, a champion, a technical evaluator, one or more influencers, and a blocker such as procurement. Buying signals fire at the account level, not the contact level, so pipeline generation only works when outreach reaches every seat rather than a single inbox.

All four provide B2B contact and company data. SalesIntel differs in three ways: contacts are AI+Human-verified with a 95% accuracy guarantee rather than sourced through automation alone; buying signals include predictive events such as funding and leadership changes alongside standard intent topics; and implementation, support, and pipeline consulting are included in the contract. Teams evaluating alternatives typically test accuracy on a sample of their own target accounts before committing.