Polish ZYNT Redefines B2B Sales Through Signal Intelligence, Attracts USD 500K

• Wrocław-based ZYNT raises USD 500K pre-seed to build signal-driven B2B sales intelligence platform
• Their AI-powered B2B sales intelligence platform focuses shifts from lead volume to timing-based, context-aware sales prioritization
• The solution employs AI, NLP, and game theory to detect buying intent signals
• The goal is to become Bloomberg Terminal for real-time B2B sales signals

This April, the Polish AI-powered B2B sales intelligence platform ZYNT announced its Pre-Seed round of investment. The investor is 24Ventures, and the amount of the round is USD 500K.

Founders with Strong Sales + Tech DNA 

ZYNT was founded in 2024 by serial entrepreneurs Cezar Reszel (CEO) and Wojciech Ozimek (CPTO). Mr Reszel spent over 12 years building and scaling sales processes at tech companies, including as an early team member at Booksy and mentor to 20+ startups at Startup Wrocław and the SWPS. With ZYNT, he combines sales experience with AI to solve a real-life problem of generating results while eliminating the time sales teams waste on the wrong leads and build a system that tells salespeople who to contact, when, and why, powered by explainable AI under the hood.

Mr Ozimek, in turn, spent over 10 years building software that addresses real business problems across diverse industries like automotive, micro-mobility, pharma, and biotech, partnering with startups, scale-ups, and enterprises across the US and Europe to navigate complex technical hurdles. His current focus with ZYNT is helping B2B companies reduce customer acquisition costs through targeted custom software and automation.

To pressure-test their ideas, they relocated to New York City, the most competitive B2B sales market in the world, and conducted about 1,200 conversations with sales professionals grinding it out in one of the toughest markets on the planet.

They concluded that top-performing sales teams no longer relied on massive lead lists but on smaller, carefully selected prospect pools where each account was deeply researched. Success was no longer about finding whom to contact—existing tools already solve that—but about identifying the critical factor: why this moment is the right time to engage a prospect in their buying journey. This insight became the foundation of ZYNT.

‘When Cezary and Wojciech first presented the concept of ZYNT to us, the solution seemed like just one of many marketing automation tools. However, the strong reputation of the project team prompted us to take a closer look. It turned out that virtually all existing solutions focus on maximizing the number of leads and facilitating contact with the right people within organizations. ZYNT, instead,  introduces a new dimension through personalization based on the timing of contact. Instead of asking ‘ to whom should we reach out?,’ it focuses on ‘when should we reach out?.’ In other words, it does not generate a large number of low-conversion leads, but rather a limited number of high-quality sales signals,’ 24Ventures’ managing partner Stanisław Rogoziński tells ITKeyMedia.

Signal-Based Sales Intelligence with Personalized Signal Interpretation

ZYNT’s solution is a signal-based sales intelligence platform that helps B2B teams identify, in addition to leads themselves, the optimal timing for outreach. It aggregates and analyzes external data sources like news, social media, job postings, and business registries to detect buying intent signals and context around prospects. Using a multi-stage ELT pipeline powered by machine learning, NLP, and game theory, it identifies which signals truly indicate buying intent. Instead of simple lead lists, users receive contextual insights and timing guidance.

‘The same signal is worth very different things to different customers. A LinkedIn post about a hiring spree at one account might be a top-priority alert for one of our clients and noise for another, depending on their ICP, market, and what ‘valuable’ means to them. Our pipeline routes every event through each customer’s own scoring logic and asks the same question: given this customer’s strategy, is acting now worth their attention? The output is prioritization that’s specific to them, not generic ‘newsworthiness.’ Mr Ozimek explains.

Interpreting buying signals, it’s necessary to validate that a signal actually correlates with purchase intent rather than coincidence or noise. ZYNT treats these signals as probability claims, not verdicts. According to Mr Ozimek, the bar to surface anything as high-priority is deliberately conservative. Further, customers rate signal quality themselves and that feedback retrains the customer-specific layer of the model: false positives don’t just get absorbed, they actively sharpen the system over time. At the same time, the platform is transparent and every signal comes with a relevance score and a ‘why it matters’ comment. Whether the prospect is ready remains up to the client’s judgment, and ZYNT influences the time to notice, not the decision itself.

Onboarding a new customer takes around 4–6 hours total over the first four weeks. It starts with an intelligent questionnaire capturing ICP, targets, and what success looks like. From there, the automated configuration pipeline sets up the right sources, and first signals start flowing within hours. ZYNT then runs a deep working session with the client team to refine what ‘valuable’ means for them. The client can expect reliably calibrated signals—meaning the signal rate is tuned to the client’s taste—within 2–4 weeks of active feedback.

Product Philosophy

According to ZYNT, three rules are applied to approach privacy, compliance, and ethical considerations when aggregating signals from multiple public and semi-public sources:

• Sticking to public or customer-authorized sources: nothing scraped from behind authentication the user hasn’t explicitly connected;
• The infrastructure is EU-hosted, GDPR-compliant by design, and strictly isolated between customers (SOC2 is on the roadmap);
• From an ethical standpoint, ZYNT only surfaces what’s already public and scores it for relevance without inferring private information.

‘We’ve deliberately killed feature ideas that pushed too far toward speculation. The line is clear: monitor what people choose to publish, prioritize it, recommend action’ Mr Ozimek shares.

Mr Reszel points out that ZYNT actually matters more in a market with less digital footprint or weaker data availability than in dense markets. The system works on quality of source, not volume. It configures a small number of highly specific sources per customer rather than broad generic feeds.

‘Dense niches like SaaS, fintech or US enterprise light up in hours, while thinner niches take longer and lean harder on the few high-signal sources that exist. What we’ve learned is that in low-density markets the value per signal often goes up, because the rep’s alternative is manual research that gets nowhere. Where the math doesn’t work yet, we tell prospects honestly upfront,’ the CEO adds.

Long-Term Vision: The ‘Bloomberg Terminal for Sales Signals’

Looking ahead, the ZYNT team believes that if every sales team starts using signal-based timing, the advantage shifts from simply having signals to having sharper signals than the next platform reading the same web. Mr Reszel is convinced that this is where ZYNT’s defensibility sits: in the depth of per-customer calibration, in a learning loop that compounds with every piece of feedback, and in fitting cleanly into the rep’s workflow. When the category commoditizes, the lead goes to whoever delivers the right signal at the right moment with zero friction.

‘Sales has begun to eat its own tail. The automation of nearly every stage of the process has resulted in recipients getting flooded with excessive and often irrelevant information, causing them to ignore communication from unknown sources. ZYNT addresses these trends. Sales teams receive a highly effective tool that significantly reduces the workload associated with low-potential leads by ranking them. Additionally, the solution is quick to implement, easy to integrate, highly intuitive, and simple to tailor to the specific needs of each client. As a result, with a clearly defined problem and solution, an experienced and complementary team, a large market, and strong traction, we decided to invest in ZYNT,’ Mr Rogoziński states.

‘A lot lands in the coming quarters, but the strategic picture is the simplest way to frame it: the three-year vision is to become the Bloomberg Terminal for B2B sales signals – the system that knows what’s happening around every target account across the open web and tells the team when to act, why it matters, and on whom. Everything we ship measures against that destination,’ Mr Reszel concludes.

To tackle a core failure in modern outbound sales: not a lack of leads, but a lack of timing precision in when to engage them, ZYNT shifts the focus from volume-based outreach to context-aware, signal-driven prioritization, it addresses the growing noise problem created by over-automated sales ecosystems. This approach has an excellent chance to redefine B2B sales efficiency by turning fragmented public data into actionable, customer-specific decision intelligence at scale.