About / Christian Prokopp, PhD
Commercial judgment. Technical depth.
Technology decisions commit a business to costs, capabilities and constraints that can last for years. I work with CEOs, founders and leadership teams to make those choices explicit and translate them into work the organisation can deliver.
Bold Data is my independent CTO and executive advisory practice, focused on technology strategy, data, AI and engineering. The board decision and the engineering detail belong in the same conversation.
Recent work: building and advising
Semaverse.ai: a research platform, end to end
I co-founded Semaverse.ai and designed and built its AI research platform for M&A and market intelligence. The work connected research agents, persistent memory, knowledge graphs and cross-source search with web crawling, document ingestion and fine-grained access controls. I also built a two-way PowerPoint workflow: corporate templates became research pipelines, and the results became branded decks.
Semaverse became a PitchBook Premium Connector partner and a Crunchbase MCP launch partner. My work included the partner integrations, work with Tracxn, and helping Crunchbase work through MCP and OAuth implementation details. Connecting a data source is only part of the job; the permissions and the workflow around it have to work too.
More on the Semaverse platform and partnerships.
Camunda: helping establish early AI product work
As a consultant through Bold Data, I helped establish Camunda’s early AI product direction, building prototypes that informed its product and technology strategy. They were used internally and subsequently demonstrated at Camunda conferences.
I built a documentation and code assistant that accounted for different software versions. Another prototype used thousands of model-generated training and test examples to fine-tune a smaller model for Camunda’s expression language, helping users write and correct code. This was early applied work: making the possibilities concrete enough for product and engineering teams to evaluate.
Early Bold Data: scale without a large team
After Holland & Barrett, I built a multi-cloud crawler and scraper single-handedly, running across Google Cloud and AWS. It collected approximately 250 million Amazon product extractions across the US, UK, Germany and other markets, at low operating cost. These were extractions, not 250 million distinct products.
The engineering worked; the commercialisation did not. I did not turn that platform into a viable business. That experience matters to my advice: proving that something can be built efficiently is not the same as proving someone will pay for it.
More on the platform and published data.
Leadership at organisational scale
At Holland & Barrett, I was Director of Engineering, Data and Analytics (CDO) from 2019 to 2021. I redirected third-party budget into an internal capability, building data engineering, business intelligence and data science teams alongside a cloud-native platform. The work supported forecasting, supply-chain decisions, purchasing and range planning.
As Partner, International Engineering Practice at Think Big, a Teradata company (2016–2017), I led a practice of more than 125 people across four continents. The responsibility covered engineering and architecture delivery, practice growth, reorganisation and integration.
At Worldpay, I worked with the CDO as interim VP Data Strategy in 2018, covering data, platforms, analytics and the operating model. As Chief Data Officer at Brady PLC (2017–2018), I led the initiative to move energy and commodities products towards cloud-native, analytics-focused SaaS.
Earlier, I was Engineering Director (CTO) at Big Data Partnership, which was acquired by Teradata. At Rangespan, later acquired by Google, I led the data team and built cloud-based data-mining and processing systems.
Since founding Bold Data in 2021, I have combined strategic advisory work with practical development. My board-level work also includes a non-executive director role supporting a global telecommunications company on technology and AI strategy.
Read selected examples of the responsibilities and work.
Why I still build
I stay close to implementation because it exposes assumptions that a proposal can hide: operating costs, integration work, brittle dependencies and the limits of automation.
In separate early LLM experiments, I built a custom tool-calling layer before the APIs I was using offered native function calling. It let a model request actions from software, rather than only return text. The point was to solve a practical limitation, not wait for a packaged feature.
Tax Shrink, Llamar and Turmberg are independent projects in progress, each with a different balance of automation and human review. They keep my technical work current; they are not client case studies.
AI changes what a team can attempt. It does not remove the executive responsibility to decide what is worth funding, what needs verification and when to stop.
A technical and commercial foundation
My PhD at Queensland University of Technology focused on machine-learning-enabled information retrieval. I also hold a master's in commerce from the University of Queensland, with work in e-commerce and semantic vector-space research. Data, search and machine learning have been part of my work well before the current wave of AI tools.
How I work
I start with the business decision, its constraints and the consequences of getting it wrong. I work through the commercial case with leadership and test the technical assumptions with the people who will have to deliver.
You should expect a recommendation, not just a list of options: what I would do, why, what remains uncertain and what would change my view. Then we agree the decisions, owners and review points needed to act on it.
My involvement can be a focused assessment, ongoing executive advice or a defined fractional CTO role. The scope and authority are explicit. I take responsibility for my advice and challenge assumptions, including my own, as the evidence changes.
Explore the ways we can work together, or email me with the decision you face and what is at stake.