Projects.
Products at the intersection of marketing, AI, and the problems I saw at scale. Each project solves something real, validated in practice.
vision-intelligence
AI marketing platform built for DACH SMEs
Problem: DACH SMEs have the data but not the speed or infrastructure to turn it into marketing action. A centralised production model reduces per-piece content time by 60–70%. A purchase-intent strategy generates organic leads within 6–12 months. But most SMEs either don't have a system at all, or operate at <20% efficiency because the data lives in spreadsheets and tooling lives in silos.
MVP covers content production and purchase-intent planning; intelligence layer is in beta with 3 DACH SME pilots ahead of public beta in July 2026.
resume-matcher
ATS optimisation for job seekers in Germany
Problem: German job seekers often tailor applications manually without knowing whether the CV language matches the role, the ATS parser, or the recruiter's first-screen criteria.
Live utility used in Berk's own 2026 job search workflow; next milestone is a public template library for German senior marketing applications.
Every project here solves a structural gap I encountered at scale. Vision-intelligence came from seeing the same content infrastructure problem repeat at BSH and VeSync. The pattern: work in the product space, observe the gap, build the tool, validate it, then decide if it's a business or a service.
Some projects stay exploration. Some become the next venture. What links them: each starts with a problem I couldn't find a good tool for, built lean, tested with real users, and priced for the mid-market where the gap is largest.
See the career pattern that led here
See how these tools
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