Case Studies

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Dimetor, an Austrian deep-tech startup, is building the future of safe and connected drone operations. Their mission: enable automated, compliant drone flights by leveraging real-time data from mobile network operators — a bold step toward integrating drones safely into national airspace.

By the time I joined, Dimetor had already built impressive technology and proven early success. But the next phase required something much bigger: scaling the system to handle data volumes and performance demands at an entirely new level. With a major partnership on the horizon with one of the world’s largest mobile network operators (under NDA), the pressure was on to ensure the platform could deliver — reliably, efficiently, and at global scale.

I joined as a hands-on technical leader and scaling specialist, working directly with the founders and core engineering team. My focus was to help the company move from “it works” to “it scales.”

I analyzed the system’s architecture and data pipelines, identified critical performance bottlenecks, and designed a clear, pragmatic roadmap to handle the next order of magnitude in data growth. I introduced structured performance testing, built simulation frameworks to replicate large-scale traffic, and worked closely with the engineers to optimize code paths and data flows.

Throughout the process, my approach was outcome-driven: measure, test, and iterate — fast. The team appreciated how we could go deep technically while staying laser-focused on business goals and customer expectations.

Working side by side with the founders, I helped bring clarity and confidence to an otherwise high-stakes technical phase. I combined strategic guidance with hands-on engineering, ensuring the team not only met the performance targets but understood the underlying mechanisms to maintain scalability going forward.

My role also included raising the technical storytelling — translating our engineering milestones into credibility with enterprise clients. This helped position Dimetor as a capable, enterprise-ready partner in a highly regulated, safety-critical space.

Dimetor successfully scaled its platform to handle unprecedented data volumes — a key milestone that unlocked collaboration with one of the largest mobile operators in the world. The company emerged from this phase with a more robust, reliable, and future-proof product, ready for global adoption.

The work laid the groundwork for Dimetor’s ongoing expansion and confirmed its place as one of Europe’s most innovative companies in drone connectivity and airspace intelligence.

Statra Sales is a US-based startup on a mission to revolutionize how solar energy products are sold. Their goal: to bring structure, intelligence, and data-driven decision-making into one of the most old-school domains — door-to-door sales.

The founders had a bold vision — use algorithmic optimization, gamification, and real-time insights to increase the performance of sales teams by up to 200%. The technical foundation was already in place, but the system struggled to scale efficiently and lacked the intelligence and usability required to manage rapidly growing data volumes and user expectations.

When I joined, the company needed a pragmatic technical leader who could cut through complexity, move fast, and make smart tradeoffs — someone to bring product, data, and engineering together into one cohesive system.

I joined as a technical advisor and hands-on executor, working directly with the founders to translate ambitious business goals into practical, scalable technical decisions. My role spanned architecture, development, and product strategy — always guided by measurable outcomes.

I helped shape and implement an intelligent platform that empowered sales managers to monitor performance, assign tasks dynamically, and leverage algorithmic recommendations to improve conversion rates. The system combined smart data processing with gamification elements that motivated sales teams, giving them real-time visibility into their impact.

On the infrastructure side, I led efforts to handle the ingestion and analysis of hundreds of gigabytes of geospatial and location data — a key requirement for mapping millions of rooftops and identifying high-value targets. Through structured performance testing, efficient data modeling, and technical simplification, we achieved high performance at a fraction of the original complexity.

Working closely with the founders, I helped establish a fast, outcome-driven engineering culture. I brought technical focus and clarity to the team — identifying what mattered most, cutting out noise, and ensuring we moved from ideas to working features in days, not weeks.

I also supported the team through critical decision-making phases — from tech stack choices to product roadmap alignment — always balancing innovation with execution speed. My approach was hands-on, transparent, and deeply aligned with the company’s commercial goals.

Within months, Statra transformed from a promising idea into a high-performing sales intelligence platform. The new system empowered teams to operate more efficiently, helped managers make data-driven decisions, and set the foundation for the company’s aggressive growth goals.

By building the right foundations and scalable infrastructure, we positioned Statra to deliver real impact — smarter decisions, faster feedback loops, and a measurable increase in sales productivity.

Amp Live Radio started as one of Amazon’s most ambitious internal startup projects — a bold attempt to reinvent radio for the digital age. The vision was simple yet powerful: bring the magic of live radio to the internet, but make it social, interactive, and creator-driven. Listeners could discover stations, host live shows, and connect with others who shared their interests — merging community with real-time audio.

When I joined, Amp was in its early startup phase, operating inside Amazon but running with the speed and uncertainty of a new venture. The challenge was clear: move fast, ship continuously, and prove value — all while navigating the complexity of a large organization.

The mission required a delicate balance between startup pragmatism and Amazon-scale reliability. That’s where I came in.

I joined as Lead Engineer and Engineering Manager, responsible for major parts of the product and the delivery of multiple backend and frontend components. I led a team of around 20 engineers, driving execution in a fast-moving, constantly changing environment.

From day one, I focused on velocity through pragmatism and simplicity. We were building something completely new, and the only way to validate our vision was to get it into users’ hands quickly. I helped the team adopt an iterative approach — launching Alpha, Beta, and MVP versions in rapid succession — each one delivering tangible learnings and measurable improvements.

I also challenged the team (and leadership) constantly with one question: “Why?”
Why build this feature now? Why invest in long-term scaling before we’ve proven engagement?
That mindset helped us focus on what truly mattered — getting to market fast and learning from real users, not internal assumptions.

Technically, we optimized for independence. I restructured how we owned services to minimize cross-team dependencies, allowing my team to move faster and deploy autonomously. I worked closely with product managers and designers to ensure alignment between business goals and engineering effort — keeping focus high and overhead low.

Leading inside a startup within Amazon meant constant context-switching: balancing innovation speed with the rigor of Amazon’s engineering standards. I created a culture where engineers were encouraged to take ownership, move decisively, and deliver iteratively — but always with quality and user experience in mind.

My leadership approach was hands-on and pragmatic: define clear priorities, empower decision-making, and remove blockers. I coached my engineers to think beyond code — to understand product strategy, to challenge the “why,” and to make technical decisions rooted in business impact.

Through strong stakeholder communication and transparent delivery, I built trust across leadership layers — from executive sponsors to peer teams — ensuring alignment even in moments of high uncertainty.

Our pragmatic, outcome-driven approach paid off. We delivered Amp Live Radio through multiple launch phases — from Alpha to public MVP — in record time. The iterative releases allowed us to validate core product hypotheses early, refine user experience based on live feedback, and scale only what proved successful.

Large parts of the technology we built — including streaming, interaction, and social discovery components — were later integrated directly into Amazon Music, influencing the platform’s social and live content features.

Amp’s story became a prime example of how to combine startup speed with enterprise scale — a lesson that continues to guide how I help startups today: build fast, learn fast, and deliver with purpose.