Pablo shares how Throxy combines AI, human insight, and proprietary data to transform outbound sales for complex industries.
Pablo, you’ve had a fascinating journey from biomedical science to building Throxy. How did your background in research and diagnostics shape the analytical way you now approach sales automation?
I began my career in oncology research, specialising in breast cancer diagnostics. When working in a lab, every decision has to be evidence-based – you can’t guess or assume, you have to prove. That means you quickly learn that progress depends on good data and rigorous processes. Those learnings shaped how I think about building systems today, and when I moved into sales, I realised that the same mindset could be applied to a completely different problem – understanding how to reach the right people inside complex organisations.
In healthcare, decisions often sit deep within networks of clinicians, procurement teams, and administrators. Seeing that level of complexity up close gave me a new appreciation for how difficult it is to connect innovation with the people who need it most. That became the seed for Throxy – using data and automation to map decision-makers more intelligently and make outreach genuinely targeted rather than a spray and pray approach.
Traditional industries like manufacturing and healthcare are notoriously difficult to sell into. What’s the fundamental problem you saw in outbound sales for these sectors that inspired the creation of Throxy?
Most sales tools were built for tech companies selling to other tech companies, and they all draw from the same sources. That means every sales rep is working with the same data, reacting to the same signals, and ultimately reaching out to the same people at the same time.
In industries like manufacturing, logistics, or healthcare, that approach breaks down completely. Many of the right prospects aren’t online at all. They generally don’t have LinkedIn profiles, some of the companies don’t even have websites, and this creates a huge blind spot for the sales teams that want to reach out to them.
Throxy was built to close that gap. We combine proprietary data, technology, and human research to uncover the real decision-makers that conventional tools can’t see. Once you can reach those overlooked buyers, outbound sales stops being a volume game and becomes something far more predictable – a system that consistently connects the right companies with the right people.
“Service-as-Software” is a unique term Throxy uses to describe its model. How does this differ from traditional SaaS, and why does it work so well for complex, relationship-driven industries?
The key difference between traditional SaaS and service-as–a-software is that traditional SaaS gives you the tools – but at Throxy, we deliver the outcome. Most platforms will provide teams with a dashboard and then they need to build their own processes. That means more time needs to be spent on setup and managing the platform. Let’s also not forget that businesses will be using more than one tool, meaning they lose time that could be spent actually speaking with prospects and customers.
With Throxy, it’s the complete opposite. Our customers don’t buy seats or dashboards, they’re buying meetings. We take ownership of the entire outbound function, powered by our own data infrastructure and AI systems.
Instead of another platform to maintain, Throxy operates as a managed execution layer that runs quietly in the background, identifying the right prospects, crafting outreach that actually cuts through, handling replies, and delivering qualified meetings.
In relationship-driven industries, every conversation needs to feel personal and relevant. By combining automation with human judgment, we make sure context, tone, and timing always feel right to the situation. Technology is doing the heavy lifting, but it’s guided by people who understand the nuance and context.
Vertical AI agents are quickly becoming the new engine behind automated sales funnels. How do you define a vertical AI agent, and what makes it so transformative compared to generic AI tools?
When most people think of AI in sales, they picture generic systems that automate repetitive tasks such as writing emails, analysing responses, or scheduling follow-ups. That type of automation helps, and it does have a role, but it rarely understands the ‘why’. If, for example, one email resonates but another doesn’t, it can’t identify why, and there could be various reasons and patterns from the tone to the time that it was sent.
Vertical AI agents are systems trained on the specific dynamics of a single sector or industry, for example signals, roles, jargon, and buying behaviours, rather than general data. Generic AI can automate outreach, but it doesn’t understand context. A vertical agent in manufacturing, for instance, knows what an RFP cycle looks like and can talk about an OEM like a professional would. That’s what makes it more transformative – it doesn’t just automate messages, it can better understand and navigate the contexts within that industry.
You’ve often emphasized that AI alone isn’t enough; it needs human oversight. What’s the ideal balance between automation and human judgment when scaling outbound operations?
AI is great at doing what people find slow or repetitive, but it still lacks the judgment that makes outreach effective. The sweet spot is where AI takes care of the mechanical work so that humans can spend their time on more important tasks, such as understanding nuance and building genuine relationships.
Automation can surface patterns, but it’s humans who can figure out what those patterns actually mean. A system might flag that a company is hiring or expanding production, but only a person can interpret whether that’s a sign of real intent or just business as usual. When people guide the system rather than simply monitor it, automation gets smarter and results improve because the feedback loop is shaped by human judgment that can read between the lines.
That’s also what makes sales roles more meaningful again. The best people don’t want to spend their days copying templates or chasing unqualified leads. Instead, they want to think strategically, use creativity, build relationships, and have real influence over the outcome. The right balance of AI and human oversight creates space for that.
Sales efficiency often depends on data quality. How does Throxy’s proprietary data infrastructure uncover decision-makers that most teams can’t even find on platforms like LinkedIn?
We built our own proprietary database. Instead of relying on LinkedIn or third-party lists, Throxy maps real-world signals to surface verified decision-makers. These include trade filings, supplier networks, certifications, web infrastructure to name a few. You might be able to uncover decision makers in online forums, reviews or even Reddit threads. We connect those dots manually and algorithmically, building a far richer picture of who actually holds buying power.
AI systems can analyze deliverability signals, adapt tone, and even reframe messages dynamically. From your experience, what’s the next frontier for intelligent sales systems beyond automation?
The next frontier is moving from reactive automation to proactive agency. Instead of just optimising what you tell it to do, AI will independently identify opportunities and take action. It’ll analyse engagement patterns across your entire pipeline to surface which prospects are showing buying signals, automatically adjusting outreach strategies based on what’s working, or even initiating conversations when market conditions or customer behavior indicate the timing is right. It’s about systems that don’t wait for instructions but use all available data to make and execute decisions autonomously, transforming sales from “automated tasks” to “intelligent action.”
Many digital transformation initiatives fail due to poor adoption or lack of engagement. How can vertical AI agents help traditional industries overcome this resistance to change?
We’ve all heard the stories of how difficult it’s been for businesses to get buy-in when adopting new tools, and that’s because the new tools often feel like another layer of work for the team. Vertical AI agents reduce friction by fitting into existing workflows instead of replacing them. They operate quietly in the background and teams experience value without overhauling how they work.
That said, even the smartest systems need the right support to be effective. You need experts who can implement them properly and guide teams on getting the most out of them. That’s where Throxy’s service-as-a-software model works so well – the technology comes with a team that understands how to deploy it, interpret it, and achieve real results. For industries wary of “tech for tech’s sake,” the combination of automation and expert support is the key to adoption.
Throxy has achieved remarkable results, $63M in pipeline and 243% YoY growth with a three-person team. What key principles or frameworks do you believe enabled this scale with such lean operations?
In the early days of Throxy we adopted a lean philosophy – fail fast, learn faster. We cut losses early, avoiding sunk-cost fallacies, and treated each misstep as a lesson banked for future success. That approach shaped how we think about scale even now. Growth isn’t about adding more people, it’s about building systems that are constantly evolving and learning.
That philosophy has carried through into how we’ve grown the company since. From the start, we used Throxy to grow Throxy, and we still do today. Our own platform powered the outbound that built our sales pipeline, helping us reach $1.5M in ARR within our first year and lay the foundation to achieve a $100M in total pipeline by June 2026. That was deliberate. If we were going to claim our model could remove the grunt work from outbound, it had to prove itself first. Running our own campaigns through the platform forced us to refine every stage, from the data quality, targeting, and tone, until it delivered consistent results. That discipline gave us a product we knew worked before putting it in clients’ hands.
Another principle is staying laser-focused on what matters. It’s what keeps us effective. Every hire, every process, and every line of code has to move the needle for clients. If it doesn’t, we don’t do it.
Finally, we’ve worked hard to preserve the culture that got us here from the small teams, fast feedback loops, and a habit of acting quickly on what we learn. We test, learn, and iterate constantly. For us, scale isn’t about headcount, it’s about closing the gap between what we learn, how we act on it, and what we deliver for our clients. That’s how we’ve been able to deliver results that feel disproportionate to our size.
Finally, as AI reshapes how businesses connect with hard-to-reach buyers, what advice would you give sales leaders looking to integrate AI-driven systems without losing the human touch that builds trust?
Sales leaders need to see AI as an amplifier versus a replacement. Automation should take care of the repetitive, low-value work that slows sales teams down – things like researching contacts, logging CRM entries, or chasing unqualified leads – so that employees can focus on the part of selling that actually creates value. That includes building relationships, understanding context, and closing deals.
At Throxy, we’ve seen that shift firsthand. When you remove the administrative load, sales teams get their time back to do what they were hired for. They spend less time copying templates and more time interpreting intent, crafting messages that feel relevant, and following up with valuable information and insight. AI can flag patterns, but it’s humans who decide which ones matter and how to act on them.
The companies that get this right will be the ones who use AI to make selling more human, not less. When you pair strong automation with judgment, empathy, and creativity, you don’t lose the human touch, you scale it.
A quote or advice from the author
Always try to challenge the status quo – in other words, if it’s broken, fix it. The easiest path is to follow what others are doing, but the greatest opportunities often lie in carving your own path. For years, sales tech was stuck in a loop of automation without progress. Rather than accept that as “how things are,” we asked ourselves how it should be. That question became the starting point for Throxy. Building a business, after all, means challenging defaults – from product design to go-to-market to internal culture – and rethinking anything that doesn’t move your vision forward.
Pablo Jiménez de Parga Ramos
Co-founder of Throxy
Pablo Jiménez de Parga Ramos is the co-founder of Throxy, the London-based startup rethinking outbound sales for companies selling into traditional industries with a “Service-as-Software” model. Before entering tech, Pablo trained as a biomedical scientist and worked on breast cancer research, where he contributed to identifying key biomarkers and developing rapid diagnostic tools. He later moved into sales, where he saw how the same analytical mindset used in the lab could solve a different problem: navigating the complexity of enterprise sales. At Throxy, Pablo eliminates the sales bottlenecks and burnout companies face at every level – helping get clients in the room with the perfect-fit prospects others can’t reach.
About Throxy
Throxy is an outbound growth partner for companies selling into traditional industries with hard-to-reach buyers. Focused on sectors like manufacturing and logistics, Throxy delivers qualified meetings through fully-managed, outcome-based outbound service – built on proprietary data infrastructure, not off-the-shelf tools. Backed by Base10 Partners, Venrex, and Y Combinator, Throxy is growing rapidly across the UK and the US.
