The most expensive AI integration is the one you rip out after six months.

When the feature doesn't fit your product, your users notice right away. They try it twice and don't come back. I come in early enough to keep that from happening: in discovery, in feature design, and in the error states nobody else remembers to build.

Successful projects with
InterhypPubtech LogoContinuumObjego

Do these problems sound familiar?

  • 01

    Your team is experimenting with AI, but nothing makes it to production

    There are prototypes, proof-of-concepts, and Slack channels full of ideas – but not a single AI feature is live. The gap between "works locally" and "running stably in production" is bigger than expected.

    Solution

    That's exactly the gap I bridge. I take validated ideas and bring them into production – with error handling, monitoring, caching, and the guardrails that turn a prototype into a reliable feature. At continuum.club, the MVP was production-ready in 3 months.

  • 02

    Internal data is not accessible to AI

    The AI model can give brilliant answers – but not about your products, customers, or processes. Without access to internal data, every AI integration stays generic and useless.

    Solution

    I build custom MCP servers and RAG pipelines that securely connect AI models to your internal data sources – with clear permissions, audit logging, and without sensitive data leaking out. MCP server development is currently a niche skill – most freelancers aren't familiar with the pattern yet.

  • 03

    Privacy concerns are blocking every AI project

    Legal has concerns, IT security is raising questions, and no one knows whether the planned AI integration is GDPR-compliant. The project is on hold.

    Solution

    I rely on API-based integrations with full control over the data flow. Sensitive data stays local, only the bare minimum goes to the model. If needed, I work with European providers like Mistral or self-hosted models via Ollama – documented and traceable for your legal department.

  • 04

    Manual processes cost your team hours per week

    Writing summaries, categorising emails, reviewing documents, prioritising support tickets – your team is doing things manually that an LLM could handle in seconds.

    Solution

    I identify the processes with the highest automation potential – not the most technically interesting ones, but those that actually give your team time back – and build LLM-powered workflows that integrate directly into your existing tools.

  • 05

    Your competitors have AI features – you don't

    Your competitors are launching AI-powered features, customers are asking for them, and your product suddenly feels outdated. But your team has neither the capacity nor the experience to integrate AI quickly.

    Solution

    I jump right in – no two-week onboarding, no learning curve for your stack. I know the common LLM APIs, embedding strategies, and deployment patterns, and deliver the first production-ready AI feature in weeks, not quarters.

  • 06

    AI responses are unreliable and hallucinate

    The model gives convincing but incorrect answers. Without guardrails and validation, every AI feature is a risk to your brand and the trust of your customers.

    Solution

    I implement RAG with controlled retrieval, output validation, and clear fallback strategies – so the feature stays silent when uncertain rather than hallucinating. Answer quality becomes measurable, not just a feeling.

Can I help you with your AI project?

Yes, if you...

  • Have an existing SaaS product and want to ship AI features in weeks instead of months – without spending months training your team on LLM APIs
  • Want to make internal data (documents, CRM, processes) accessible to AI without losing control over sensitive data
  • Have a small dev team that needs senior capacity who thinks along immediately – architecture, deployment, and product logic included

Probably not, if you...

  • Don't have a clear use case yet – I implement, but don't advise at a strategic level on which AI idea to pursue
  • Are building a greenfield AI product without existing infrastructure – my focus is on integration, not greenfield development
  • Are only looking for one-off consulting or a brief audit without subsequent implementation

How I help

I'm Nils – Senior Product Engineer based in Bochum, specialising in integrating AI into existing SaaS products and web applications.

I don't build demos that look good at conferences. I build AI features that run in production – with error handling, monitoring, and the guardrails a SaaS product needs. My focus is on the bridge between the AI model and your existing system.

What sets me apart:

  • Fullstack + AI: I don't only think in prompts, but in architecture, APIs, and deployment. No "throwing it over the fence" to your backend team.
  • MCP Server Development: I build custom MCP servers that securely connect AI models to your internal systems – a skill set hardly any freelancer offers today.
  • Production-ready from day 1: Every feature ships with monitoring, logging, and fallbacks – not as a fragile prototype.
Nils Schlüter

My tech stack for AI integration:

TypescriptNext.jsNode.jsPostgreSQLDockerVercel

Successfully implemented for

From idea to production-ready AI feature

  1. 01

    Discovery & use-case analysis

    Together, we identify the use cases with the greatest business impact. I analyse your existing infrastructure, data sources, and requirements – and create a concrete implementation plan with a clear scope and timeline.

  2. 02

    Development & integration

    I develop the AI feature iteratively and integrate it directly into your existing system. RAG pipeline, MCP server, LLM integration – everything is built production-ready, with tests, monitoring, and documentation. You see progress through regular updates.

  3. 03

    Launch & monitoring

    After launch I monitor the AI feature's performance, optimise prompts and retrieval quality, and make sure everything runs stably. I document everything so your team can continue developing the feature independently.

Testimonials

There aren’t many true full-stack developers. Fewer still can take on deeply complex problems and genuinely solve them. Nils is both, and more. He brings technical depth, clarity of thought, and a calm, reliable presence to every project. A highly respected and recommended addition to any team. And when he’s not coding, he’s out training for triathlons; a true embodiment of work hard, code hard, play hard. On all fronts, Nils is a machine.

Hira Verick
Hira VerickDesign / Technology / Strategy @ continuum

At objego, I worked with Nils in different teams and phases of the company - from greenfield features to legacy migrations. What always impressed me was how quickly he could slot into new setups and immediately start contributing real value. He brings a strong mix of technical depth, calm communication, and the flexibility to adapt to changing requirements. You always felt in good hands when Nils was involved.

John Drake Brockman
John Drake BrockmanChapter Lead @ ista

Nils war einer der ersten, die unser Produkt technisch mit aufgebaut hat. Mit seiner strukturierten Arbeitsweise, Flexibilität und klaren Kommunikation hat er maßgeblich dazu beigetragen, dass wir schnell vom Konzept zur funktionierenden Lösung kamen. Besonders wertvoll war seine Fähigkeit, Unklarheiten in Anforderung proaktiv und kreativ zu lösen und ein gutes Auge für UI.

Jurij Peters
Jurij PetersCo-Founder & CEO @ eco.income Engineering GmbH

Tell me about your project

Want to talk about your project? Feel free to reach out via the form or:

Here's how it works

  1. 01

    A no-obligation conversation about your project

    We'll discuss your project and I'll show you how we can tackle it together.

  2. 02

    Concept and proposal

    I'll create a detailed concept with a clear timeline and a transparent offer.

  3. 03

    Fast execution

    From concept to working solution with regular updates and clear communication.

Frequently asked questions