It's my mission to help you get the best out of Your Business.
My name is Eetu Rantanen. I'm a developer with over 13 years of professional experience. Game development is my main focus, alongside web development, data and analytics, and AI solutions. I also hold three academic business degrees.
I'm available for hire and taking on new projects. Based in Tampere, Finland, I work remotely with clients anywhere in the world. I take on contract and freelance work, and I'm open to a more permanent role for the right project.
Hire meWhat I can do for you
Here are the main areas I work in. If you're planning a project in any of them, I'd like to hear about it.
Game & Web Development
Games, web applications, developer tools, and back-end services for desktop, mobile, and web.
I take projects from the first prototype through to a finished, shipped product.
Data & Analytics
Data pipelines and analytics for desktop, mobile, and web.
I collect, process, and turn raw data into actionable intelligence: clear answers about your customers and your product.
AI Solutions & Consulting
Custom AI tools, chatbots, and applications built around your data, your brand voice, and your guardrails.
I've put AI to work for clients since 2023, and I'll tell you straight where it fits and where it doesn't.
My Services in Detail
Built, shipped, and kept running
Games, developer tools, web apps, and back-end systems. One developer who can take any of it from idea to production.
Games
Game design, development, and live ops for desktop, iOS, and Android. Primarily Solar2D and Unity, with experience across several other engines. No art, no audio; everything else from prototype to launch. In my career I've helped maintain tens of mobile games with hundreds of millions of combined downloads.
Developer tools
Internal tooling, editor extensions, automation, and build pipelines: the kind of work that pays for itself by making everyone else on the team faster.
Websites and web apps
Marketing sites, custom web applications, and back-end services, full stack from prototype to deployment. More in the .
Back-end systems and dashboards
Servers, APIs, back-end services, and the online dashboards built on top of them: the systems that keep a product running once it ships. The data side of this, the pipelines, processing, and analysis, is its own discipline; more in the .
A website that earns its keep
I take on web work selectively, for clients who want it done properly, not just done. That covers web design, technical SEO, usability reviews, and WCAG-compliant accessibility, alongside the development itself.
A website needs a purpose
Before anything gets designed, the real question is what the site is for. A sales funnel? Lead generation? Educating customers, or building enough trust to close the deal offline? The answer drives every decision after it: structure, copy, what the page asks a visitor to do, what counts as success. A site built without that answer is just decoration. I work the purpose into the design from the start, so the site does its job reliably.
If Google can't find your site, neither will your customers
A site that doesn't show up in search is invisible. For most small businesses, search is the single biggest path to discovery, and even ads, referrals, and word of mouth usually end with someone Googling your name.
There's no shortcut and no "secret"
Ignore anyone selling "#1 on Google" or insider tricks; nobody has a back channel to the algorithm. Search engines reward sites that are technically sound, well structured, and genuinely useful, full stop. The tricks age into liabilities the moment the algorithm shifts.
Design, performance, accessibility, and SEO are one job
Page weight, semantic markup, contrast, heading structure, mobile layout: the same decisions move all of them at once. So I treat them as a single piece of work, priced as one.
Data into decisions, not noise
Data done well tells you who your customers are and what to do next. Data done badly is noise, or worse, a regulatory and reputational liability.
What I build with data
The deliverables are concrete: data pipelines that ingest and transform raw events, analytics dashboards that put the answers in front of the people making decisions, and custom tooling built on Python's data, AI, and ML libraries. I have built and run these for client work and for my own projects, end to end.
Data is potential, not an asset
Raw events sitting in a database don't move the business. Data becomes an asset only once it's collected, processed, and analysed into something you can act on: who your customers are, what they actually do, which features matter, where the funnel leaks. That conversion is the work I do.
Garbage in, garbage out
Track the wrong events, mistag them, or capture inconsistent identifiers, and every report built on top inherits the defect. Designing the collection layer well matters as much as the analysis.
Knowing what not to track
Collecting everything because storage is cheap is a bad default. Every event you capture is something to store, secure, document, and justify to a regulator. This very site is the example: no cookies, no analytics, no trackers, because nothing here would justify them. Sometimes the right amount of data is none.
If you don't actually process and analyse the data you've collected, and then make data-driven decisions, then you should not collect any data to begin with. It'd just be a liability and a waste of resources.
Privacy is non-negotiable
Collecting personal data is a commitment: a privacy notice, a lawful basis under GDPR, data subject requests, breach handling, retention limits, processor contracts. None of it is optional.
AI makes this sharper. Every document, dataset, or transcript fed into an LLM is data leaving your control. That can mean your own corporate secrets, or your customers' personal data, leaking through a tool nobody audited. Privacy now covers what your team hands to AI, not just what you collect from users.
Where AI fits, and where it doesn't
I build practical AI: chatbots, assistants, and tooling that does real work. The hard part is rarely the model. It's knowing exactly where AI earns its place and where it's a liability, and that judgement is what you're hiring.
Custom chatbots and assistants
I build production AI chatbots: customer support, internal Q&A over your own documents, lead capture, guided onboarding. Built around your data, your brand voice, and your guardrails. Not a generic ChatGPT box; an assistant that knows your product and stays in its lane.
Claude workflows and AI tooling
AI inside the engineering process itself: agent-driven research, data extraction pipelines, document understanding, code generation and review, automated quality checks. Tooling that compounds your team's output, not the kind that just demos well.
Scoping it right is half the work
AI is a pattern-matching engine, not a thinking machine. It's superb with language and messy data, and unreliable anywhere a confident wrong answer carries real cost: audit-grade certainty, legal liability, decisions you can't verify. Knowing that line, and scoping a project to stay on the right side of it, is most of what separates an AI project that ships from one that quietly fails.
AI should empower people, not replace them
I build AI to make a team faster and cheaper to run, not smaller: a force multiplier for the people you already have. I won't take on work whose goal is to cut staff, or to put a number on a layoff that's already been decided. AI also carries real costs that never reach the invoice: an environmental footprint, social consequences, ethical questions with no clean answers. If you want your people to do more, not to have fewer of them, that's the work I want.
You've read what I do and how I think. Now tell me what you're building.
Hire meHere's some of my earlier work
A curated selection of past projects is on the way. In the meantime, my GitHub and game design portfolio show plenty, and I'm glad to share work relevant to your project directly.