How Tal Peretz built the most talked‑about company in sales tech

Photo courtesy of Tal Peretz

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In an era where generative AI promises to reinvent every corner of business operations, sales technology has become one of the most crowded and most confused frontiers in enterprise software. From “AI‑powered” outreach bots to lead scoring widgets, companies have flooded the market with tools that promise to deliver more meetings, more conversions, and more revenue. Yet many fall short on tangible outcomes. Into that fractured landscape stepped Onfire AI, a vertical, context‑driven platform that has rapidly become one of the most discussed startups in sales tech.

Founded and led by CEO Tal Peretz, Onfire is a sales tool that fundamentally rethinks how artificial intelligence should assist revenue teams, especially those selling into technically complex markets. Instead of augmenting generic CRM data with superficial signals, Onfire crafts what it calls an Account Intelligence Graph™, a real‑time, dynamic understanding of buyer intent, context, and behavior drawn from both external digital signals and a customer’s own sales data.

A different kind of sales AI

Before Onfire’s official launch in 2025, many AI sales platforms focused on automating workflows or generating outreach copy. These platforms often promised personalization, yet lacked the deep, verifiable context that complex sales require. McKinsey & Company reported that while more than three‑quarters of enterprises claimed to be using AI, roughly 80% saw little to no material improvement in core business metrics like sales performance or productivity.

Peretz and his co‑founders, Shahar Shavit (CTO) and Nitzan Hadar (CPO), approached the problem differently. All three bring a background in Israel’s elite intelligence unit, 8200, where extracting signal from noise is mission‑critical. Rather than bolt AI onto existing sales data, they placed vertical data analysis at the very center of their product: AI built on a foundation of purpose‑collected, domain‑specific signals from developer forums, product reviews, technical discussion groups, and vendor evaluations. 

This vertical, context‑first design underpins Onfire’s capability to detect real buying intent, not the proxy metrics such as page views or email opens that traditional platforms rely on, but conversations and behaviors actually relevant to purchase decisions in IT infrastructure and software markets. It’s a level of granularity that resonates with teams selling to DevOps leaders, CISOs, and technical procurement professionals, whose purchase decisions are rarely dictated by surface‑level indicators.

From stealth to significant traction

Onfire’s ascent has been swift. After over two years in stealth development, the company officially emerged in October 2025 with a $20 million funding round co‑led by Grove Ventures and TLV Partners, with participation from IN Venture and LeumiTech 77. According to reports, a $14 million portion of the raise was considered a Series A, and the funds are earmarked for expanding AI capabilities, R&D, and go‑to‑market efforts across Israel and the U.S.

Even before that public launch, Onfire’s impact was measurable: early adopters, including Aiven, Spectro Cloud, Cyera, Port, and ActiveFence, have leveraged the platform to uncover signals that traditional systems miss. The company claims to have helped its clients drive over $50 million in closed deals in just 12 months of beta operations, an impressive early outcome in a sector where proving ROI can be notoriously difficult. 

Interviews conducted by Peretz and the founding team with 275 revenue leaders before Onfire ever wrote a line of code shaped the product’s fundamental thesis: sales teams crave clarity, not complexity. It’s why Onfire’s models are built to understand who is in the market, and why and when they’re engaging to complement internal CRM activity with real‑world, real‑time behavioral intelligence drawn from public and proprietary data. 

Scaling precision in a noisy market

What sets Onfire apart is its insistence that context matters more than scale. Where generative platforms can drown sellers in noise, Onfire’s vertical AI aims to deliver actionable insights at the moment they matter. Its dataset reportedly covers technographic information for 91% of global companies, enabling nuanced prediction and targeting strategies that align tightly with evolving buyer journeys.

As AI adoption continues to proliferate across enterprise sales stacks, the broader market is watching how vertical specificity will shape the next generation of revenue tools. According to industry analysts, the AI for the sales and marketing market could grow substantially over the coming decade, driven by solutions that deliver measurable outcomes rather than abstract promises. 

Tal Peretz’s blueprint for lasting impact

Tal Peretz’s leadership reflects a blend of analytical rigor and practical sales insight. By focusing first on the problem of context, then building an AI platform that operationalizes precision at scale, Onfire has carved out a distinct position in an otherwise crowded space. It’s a rare example of AI that doesn’t just augment workflows but fundamentally redefines how revenue teams think about buyers, intent, and opportunity.

Today, Onfire stands not merely as a new entrant, but as a bellwether for what the convergence of data science and sales strategy can achieve when intelligence isn’t an afterthought, but the product’s foundation.