Recurring customer requests to automate
FAQ, support tickets, first contact — when the same questions come in daily, they're a job, not fate.
FAQ, support tickets, first contact — when the same questions come in daily, they're a job, not fate.
CRM, email, calendar, Excel — when staff copy data from A to B, it consumes hours without creating value.
On the website, by phone, in the messenger — multilingual, with clear handover to a human when things get complex.
A central control point for your tool landscape — instead of licenses sitting next to each other without talking.
Staff find answers in seconds — in SharePoint, Confluence, Google Drive or your own document base.
You don't want a pilot project that vanishes into a drawer. You want something that delivers value tomorrow.
No standard templates. We build systems that fit your business — from single AI components to complete solutions.
On your website, in Messenger, in Intercom — chatbots that answer customer questions instantly and pass qualified issues to the team.
Inbound calls captured structurally — even nights and weekends. Note lands in CRM, sales only sees warm leads.
Your tool landscape (CRM, email, calendar, accounting, databases) connected in a central control point. Hours per week back.
Staff ask in natural language, the system answers from SharePoint, Confluence, Google Drive or your knowledge base — with citations.
Custom web applications, internal tools, dashboards — when standard solutions do not cover your processes.
We analyze your processes together: Where is time lost? Which tasks repeat? Where would AI be economically sensible?
Concrete implementation plan: which solution, which systems, in what order. With effort, risks, and ROI estimate.
We build the solution — chatbot, voice agent, automation, internal tool or combination. Cleanly connected to your existing systems.
Clear handover with team training, documentation, playbooks. Optional maintenance contract for the time after.
Staff ask in natural language, the system answers from Confluence, SharePoint, Google Drive or your document base — with citations.
On the website, in the messenger, in Intercom — answers standard questions, qualifies inquiries, hands off seamlessly to your team when it gets complex.
Inbound calls are structured: need, timing, budget. Note lands in CRM, sales only sees leads that are really ready.
A central hub: CRM, email, calendar, accounting, Slack — connected, triggered, documented. Without breaks, without manual click-work.
Representative build patterns from our practice. Concrete references discussed in the initial call — under NDA.
Example assumption: around 75 % automation rate for clearly recurring, rule-based tasks — as a rough guide. Real values depend on process depth, data quality, and integration maturity and are validated in the potential analysis.
Validate your own potential →Tool follows task — we pick the right combination per project, not the trendiest.
DH · Index
Bodensee · 2026
My job is translating the complicated into the working — and back again, when someone has to explain it.
Four years of focused practice at the intersection of AI, data and operational processes — supplemented by continuous training, including as an IHK-certified AI Implementation Manager. HeltAIum was born from a simple observation: good AI implementation isn't expensive. Bad AI is.
I work with a small, fixed circle of specialists — architecture, infrastructure, security, UX. No middle managers, no slide factories. When I say yes to you, I'm the one doing the work — in DACH or Hungary, in German, English or Hungarian.
Good AI implementation isn't expensive. Bad AI is. That's why we invest more time in discovery than most competitors do in the entire project — before anyone writes code.
We don't promise six weeks for something that honestly takes four months. Speed sells well — but only once. Reliability sells for twenty years.
Model choice is a technical decision — not a religious one. Claude, GPT, open source. We take what fits the task. And we say why.
We leave when your team is sovereign — not an hour earlier. Handover isn't the end of a project. It's the reason there was one.
An honest assessment. What's feasible, what's wise, in what order — within a few days you'll know, in writing.
The core of our work. We design the system, build the prototype, validate with your data — you decide with evidence.
Full implementation with handover. We build, document, train — and stay reachable for three months after go-live.
Every engagement is individually scoped · fixed price from Phase II · proposal within 5 business days
Two approaches depending on scope: Quick-start projects (a single chatbot, voice agent, or n8n workflow, clearly scoped) take 4–10 weeks. Custom AI architectures (multiple systems, data, compliance, agent orchestration) take 2–9 months. The potential analysis as entry point delivers results within a few days. Which path makes sense for you we clarify in the initial call — we won't promise four weeks for something that honestly takes three months.
All three. Model choice is a technical decision, not a religious one — it depends on latency, cost, data protection and task profile. In practice we often build hybrid architectures: Claude or GPT for reasoning-heavy tasks, local open-source models for sensitive or high-frequency paths.
Then start with the potential analysis. That's exactly what it's for: a sober look at where your levers are, where they aren't, and which two or three initiatives are actually worth it. No one should start a six-figure project without those questions answered.
Yes, we have experience with all three. For regulated industries we prefer locally hosted open-source models, isolated vector stores, full audit trails. If a US model is strictly required, we clear the legal situation with your legal team in advance — in writing. EU AI Act included.
Yes — perhaps especially. Mid-market companies often have the decisive advantage: short paths, clear decision-makers, no endless consulting theatre. We deliberately use the potential analysis as an entry point — an honest option for mid-market leadership teams, not a political battle.
Yes, actively. HeltAIum serves clients across the entire DACH region as well as Hungary. Consulting, workshops and deliverables in German, English and Hungarian — on-site or remote. Compliance topics for Hungarian banks (MNB) and the EU AI Act are part of our practice.
Mid-sized companies and enterprises across DACH and Hungary: manufacturing and engineering, trades and construction, professional services (tax/legal), healthcare practices, B2B services, regional FinTech and banking. We are especially strong on cross-border DACH-HU operations.
It will make mistakes — every system does, every human does. The right question is: which mistakes are acceptable and which are not. We build with clear escalation paths: hard cases (legal, financial, safety-critical) always go to a human. For soft cases there are confidence thresholds, audit logs and a correction loop where your team improves the answers. We also start with pilot phases where the AI suggests and a human approves — until quality is provably right.
Three concrete differences. First: We start with the potential analysis as a small paid step — you have a usable deliverable (diagnostic document) before committing to a larger project. Second: We deliver code and documentation you can keep running without us — no vendor lock-in, no black box. Third: IHK-certified, one stable point of contact (Daniel Helt), not a rotating junior team. When something doesn't work, you know who to call.
A short, free initial call. You describe what you have in mind — we say if and how we can help. Honest, without sales theater.