In a year defined by AI-driven promises across every business sector, one company is taking a different path. Tel Aviv-based Onfire has secured $20 million in funding, co-led by Grove Ventures and TLV Partners, with participation from IN Venture and Leumi Tech by Bank Leumi.
Unlike the flood of horizontal AI tools that promise automation and volume, Onfire is focusing on precision. The company’s Vertical AI platform, designed specifically for IT sellers, has already helped SaaS customers generate over $50 million in closed deals in just 12 months since launch.
Its goal is clear: to replace noisy, generic intent data with insights that accurately reveal who is ready to buy, when, and why.
Why Most AI for Sales Still Misses the Mark
Despite the hype, many businesses still struggle to turn AI investments into revenue impact. According to McKinsey & Company’s 2024 “State of AI” report, 78 percent of companies use AI in some form, yet over 80 percent have seen no significant improvement in top- or bottom-line performance.
The issue, experts argue, is not adoption but application. Generic AI models lack the depth to understand industry context. They generate surface-level predictions that fill CRMs with incomplete data, creating more work for sales teams instead of less.
Another McKinsey analysis reinforces this point, noting that organizations can only unlock true value when AI is embedded in how teams make decisions and interact with customers. Onfire is built entirely around that philosophy.
A Vertical Model Built for Real-World Complexity
Founded by Tal Peretz, Shahar Shavit, and Nitzan Hadar, Onfire emerged from a clear hypothesis: AI in sales can only deliver measurable outcomes when it is deeply rooted in a single vertical.
To prove the concept, the founders conducted 275 interviews with revenue leaders who sell to IT buyers. The findings revealed a pattern of fragmented data, incomplete insights, and CRMs that fail to reflect how complex buying decisions are actually made.
Onfire’s answer is a contextual, data-layer-first system. It merges third-party intelligence—product reviews, community discussions, vendor evaluations—with a company’s internal sales context. The platform then builds a continuously updated “map” of the IT market, showing how decisions flow across teams, budgets, and compliance processes.
Understanding How IT Buyers Really Buy
The IT infrastructure ecosystem is one of the toughest markets for sellers. Decisions often involve multiple stakeholders, security reviews, and long procurement cycles. Traditional AI tools treat these interactions as isolated data points. Onfire interprets them as connected signals.
By analyzing the tech stack of 91 percent of companies worldwide, Onfire can identify moments that truly indicate intent, such as early-stage vendor comparisons, product migrations, or team-level discussions in technical communities.
This approach allows sales teams to focus on opportunities with genuine conversion potential instead of chasing cold signals. The results, according to customer data, include faster deal cycles and improved meeting conversion rates.
Investors See the Next Evolution of Go-to-Market AI
For investors, Onfire represents the next evolution in AI for go-to-market (GTM) teams: precision over volume, context over automation. The company’s vertical model creates a compounding data advantage. Each interaction enriches its understanding of IT buyer behavior, strengthening predictions and accelerating time-to-value.
The founders’ background in AI and entity resolution also gives the platform an edge in accuracy, helping it bridge the long-standing gap between external market data and internal CRM records.
As a result, Onfire is positioning itself as the default GTM intelligence layer for companies selling to technical buyers: a $5 trillion global market that is still underserved by existing sales technologies.
The Road Ahead: Turning Data into Direction
The real test for Onfire will be scaling its precision model without diluting it. Research shows that up to 95 percent of AI projects fail to scale beyond pilot phases.
To stay ahead, Onfire must prove repeatable ROI across a broader customer base while maintaining its vertical focus. If it succeeds, it could set a new benchmark for how AI-driven platforms define value creation in enterprise sales.
The Shift from Activity to Accuracy
AI in sales is entering a new phase, one where success is measured not by how many leads a system generates, but by how accurately it identifies the right ones.
Onfire’s rise signals that shift. By rebuilding the sales data layer around precision and context, the company is showing what the next generation of GTM AI could look like: intelligent, vertical, and directly tied to revenue impact.
For a market long defined by automation overload, Onfire’s model represents something rarer and more valuable: clarity.
About Onfire
Onfire is an intelligent sales platform built for teams that sell to technology-driven organizations. Using advanced machine learning, it scans and interprets data from sources like online reviews, industry discussions, and vendor comparisons, then connects those insights with internal sales data. The result is a clear understanding of which prospects are ready to buy and why. With automatic updates to CRM systems, Onfire ensures sales teams always have the most accurate and current view of their pipeline and market landscape.
