Five De-Risked Investment Opportunities in Tech & Gaming
I have led technology projects at scale, including serving as
Tech Lead at Porsche Germany and
Tech Lead & Delivery Manager at And Digital. Across
both corporates and startups, I have launched over 100 apps and systems.
Backed by a trusted team and proven infrastructure, I am positioned not
as an "idea man," but as an operator who delivers execution — with AI
and cloud as my core expertise.
What follows are five carefully selected opportunities across
productivity, wellness, edtech, and gaming. Each is designed with
flexible investment ranges – from controlled entry points to
multi-million scaling – with execution buffers built in to protect
quality and maximize ROI. Together, they form a portfolio approach that
can be pursued individually or in parallel, depending on appetite.
Portfolio at a Glance
The portfolio is intentionally spread across short-cycle apps and longer-term platforms.
Each category leverages AI as an execution pillar — not hype, but applied
intelligence that drives user retention, habit formation, and monetization.
This balance provides immediate traction while building durable, scalable assets.
Productivity 15%Wellness 15%EdTech 40%Story Game 10%Casual Game 20%
Hybrid work and information overload make productivity apps a €20B+ market, primed for AI-driven prioritisation.
AI To-Do Tracker (Productivity)
Most task apps collect lists but don’t solve execution. This tracker
uses AI timing & prioritization
(based on attention/memory science) to notify at the right moment,
raising completion rates and retention.
De-Risking: Built on reusable backend and UI
libraries, lean MVP can launch fast, with AI delivering a clear
differentiation. UA spend scales only after retention validated.
Budget Allocation
Dev 25%UA 65%Ops 10%
ROI Scenarios
ConservativeBaseAggressive
On a conservative trajectory the investment is covered in roughly two years as professionals adopt the tool for steady subscription use. A base scenario leverages AI timing and habit reinforcement to drive completion rates and reach 5–8x returns in 24 months, reflecting the size of the productivity market. An aggressive path sees adoption at scale as AI task coaching becomes mainstream, unlocking 15–20x upside and expanding beyond individual users into enterprise productivity solutions.
Beyond productivity, wellness apps are surging — habit-driven and ripe
for AI coaching.
AI Journaling App (Wellness)
Journals fail when too demanding. Our solution uses
AI-guided prompts and
adaptive summaries
to become a “personal mentor” — one minute daily entry, long-term
insights.
De-Risking: Minimal AI prompt system & summarisation
already prototyped. Lean cohorts prove retention before UA scale-up.
Budget Allocation
Dev 25%UA 65%Ops 10%
ROI Scenarios
ConservativeBaseAggressive
In a conservative path the investment is recovered in about two years through steady subscription retention and the natural stickiness of productivity tools. A base case builds on compounding habits and AI-driven engagement to deliver 5–8x returns within 24 months, supported by the size of the productivity market. In the aggressive scenario, broader adoption of AI-enabled personal assistants positions the tracker for 15–20x upside and potential leadership in the category.
Education is slower burn but more durable — AI in coding education is
the next platform shift.
Applied Coding Platform (EdTech)
Most coding sites are abstract. This platform provides
AI-powered lab guidance and
scoped cloud envs, teaching real-world dev skills.
AI adapts challenges per learner.
De-Risking: Infra & orchestration re-used from prior
systems. Scales from lean pilot to flagship platform.
Budget Allocation
Dev 30%UA 60%Ops 10%
ROI Scenarios
ConservativeBaseAggressive
In a conservative scenario the platform recovers investment in around three years through steady subscriptions and selective B2B sales. A base case scales to 6–10x ROI in 30 months as learners adopt industry-ready coding modules with AI tutoring support. The aggressive path positions the platform as a cloud IDE with AI-managed environments, driving international adoption and enterprise deals for 15x+ returns and durable market presence.
Interactive entertainment is evolving — AI makes branching narratives
adaptive and replayable.
Adaptive Story Game (Entertainment)
Static branching games lack replayability. This title uses
AI-curated narrative branches
to deliver evolving, replayable storylines with quality control.
De-Risking: Narrative frameworks reused. Lean launch
with scalable UA.
Budget Allocation
Dev 35%UA 55%Ops 10%
ROI Scenarios
ConservativeBaseAggressive
In a conservative outcome the game pays back in two years via steady story-driven purchases and a loyal niche audience. A base case pushes 5–7x ROI within 24 months as AI-curated branching adds replay value, extending monetisation cycles. Aggressively, the title captures cultural momentum in AI-generated content, unlocking franchise-level opportunities and achieving 12–15x upside in the interactive storytelling genre.
Finally, one of the most proven casual genres — AI progression in bubble
shooters amplifies retention and monetization.
AI-Enhanced Bubble Shooter (Casual Gaming)
Bubble shooters are simple but proven cash engines. By adding
AI-driven difficulty curves and
curated retention, we increase lifetime value and
scale faster.
De-Risking: Proven infra, UA pipelines, and
publishing frameworks. Capital scales portfolio rather than single
title.
Budget Allocation
Dev 30%UA 60%Ops 10%
ROI Scenarios
ConservativeBaseAggressive
Conservatively the game delivers safe monetisation, reaching 2–3x ROI in two to three years. In the base scenario adoption follows the proven casual gaming curve, boosted by AI-driven difficulty tuning, achieving 8–10x ROI within 24 months. An aggressive path transforms the title into a flagship AI-powered casual game, scaling globally with 15–20x potential and portfolio-level impact beyond a single hit.
Optional Parallel Execution
We can run 2–3 tracks in parallel using shared AI platform components, backend services,
analytics, UA and live-ops. This diversifies risk and accelerates time-to-learning while keeping
capital stage-gated.
What runs in parallel
Shared AI stack: prompting, evals, safety, analytics.
