AI talks & training
Get your team genuinely up to speed with AI, not a lecture
An AI workshop built around your own work, not slides about the future. Your team works in the tools themselves, learns what's safe under GDPR and the AI Act, and walks out with use cases it can put to work the very next week.
- Built around your own use cases
- Hands-on, no slides
- Do's and don'ts for GDPR & the AI Act
In short
AI training for a business only works when it's about your own work. We don't do a lecture about the future of AI. We put your team on the tools (OpenAI and Claude) using real tasks from their day, show where it goes well and where it goes wrong, and hand over a practical set of do's and don'ts around GDPR and the AI Act. You walk out with use cases you'll use the next week, and if there's a real opportunity in there, we build a small trial on it together. No numbers promised that we can't deliver: this is a session, not a sales pitch.
What gets in the way
Most AI training is an hour of staring at slides about what's possible, after which everyone goes back to work and nothing changes. We don't believe in that. We build with these tools ourselves: Simply, our own recruitment platform, runs on a set of AI automations we built from the ground up. That's what makes a session with us different. We know where AI genuinely saves time and where it's playing you for a fool. In a training or talk we put your team on your own work: writing a quote, working through an inbox, setting up a report. You learn to do it yourself, not watch someone else do it. And you get an honest answer to the question that actually matters: where is this allowed, where is it not, and when is AI simply the wrong tool for the job. We think along with you: we listen first to what you want to achieve now and where you are heading, then choose the technology to match, for the most scalable and powerful result that is cost-efficient at the same time.
A team that distrusts AI, or wildly overrates it
One half thinks AI is coming for their job, the other half thinks it does everything flawlessly. Neither is true, and both stall any progress. A session where people try it themselves on their own tasks clears that noise: they see with their own eyes what it can and can't do.
Expensive tools sitting unused
You've bought licences for ChatGPT or Copilot and almost nobody uses them, or only for a laugh. The problem is rarely the tool, it's that nobody tied it to the real work. Without a concrete first use case, it stays at good intentions.
Nobody knows what's safe under GDPR and the AI Act
Can you paste a CV into ChatGPT? A client email? A contract? Out of uncertainty, half your team does it on the sly anyway and the other half won't touch it. Both are a risk. What's missing is a clear line: this yes, this never, and this only this way.
Buzzing after the demo, Monday nothing's changed
A good talk sparks energy that's already faded by Friday afternoon. Without something concrete in hand, a use case of your own, a way of working, a first trial, everyone falls back into the old routine. Inspiration with no follow-up is wasted time.
What we build
How we help
Hands-on sessions on your own use cases
Not generic examples, but your work. We ask upfront which tasks cost time and build the session around them: your team prompts in OpenAI and Claude themselves, on a real quote, inbox or report. They learn by doing, not by listening, and see straight away what works on their own material.
An honest picture of what AI can and can't do
We show just as plainly where it goes wrong: where a model talks convincing nonsense, where it misses the house style, where you really have to check the output. Because we build with these tools ourselves, we know the pitfalls from practice. Your team learns to trust AI where it can and distrust it where it should.
A practical set of do's and don'ts
You take home a one-pager nobody needs to study to get: this you may put into an AI tool, this never, and this only this way. Tailored to your situation and to what GDPR and the AI Act ask of you, in plain language instead of legalese.
A shortlist of use cases that actually pay off
By the end of the session there's a short list of tasks where AI can demonstrably save you time, ranked by effort versus return. Not a list of a hundred ideas, but the two or three that are worth starting with.
A path to a small trial (PoC)
If there's a use case worth it, we build a small trial on it together: a contained automation or application that lets you see whether it works before you invest big. That way the energy from the training isn't lost, it becomes something concrete.
Our approach
From idea to working software in four phases
Every project runs through the same four phases, so you always know what's happening, what comes next and what it costs — from first call to live software, usually in weeks rather than months.
- 01 Phase 1 Free intake
Understand & analyse
Everything starts with a good conversation. We map your goals, processes and the bottlenecks worth solving — no sales pitch, just an honest read on where the biggest win sits.
- 02 Phase 2 Free blueprint
Blueprint & quote
We turn the analysis into a blueprint: a clear plan showing exactly which steps we'll take and why, paired with one fixed quote. You know up front precisely what we build, what it costs and when it's done — no open ends, no hourly billing, no surprises afterwards. And getting that blueprint is completely free, no obligation.
- 03 Phase 3 Prototype in days
Build, test & deploy
Then we build, in short iterations. You see a working prototype in days and a finished product in weeks. We work on a modern, AI-native and secure stack — with data protection and GDPR in mind from day one.
- 04 Phase 4 100% your code
Implement & optimise
We launch, hand over the full codebase and keep improving on your terms. You get 100% ownership of the code we write — no lock-in, no licensing games. Hosting and maintenance are optional, never required.
What you always get
Fixed price
Agreed up front, never an open end.
100% code ownership
Your code, fully yours, no lock-in.
Live in weeks
Prototypes in days, finished in weeks.
Modern & secure
A scalable stack that always integrates with the latest tech. Secured by our in-house cybersecurity experts.
Tools & tech
We're not tied to one model or platform. We pick the AI approach that fits your data, budget and goal — an off-the-shelf model, a custom pipeline, or a mix — and we're honest when simpler tech does the job just as well. No hype, no lock-in.
What you get
- A hands-on AI session or talk, on site or online, built around your own use cases
- A programme agreed in advance around the tasks that genuinely cost you time
- A live demo on real examples in OpenAI and Claude, including where it goes wrong
- A one-pager of do's and don'ts around GDPR and the AI Act, in plain language
- A shortlist of use cases, ranked by effort versus return
- Working example prompts your team can use the very next week
- Advice on whether a first use case lends itself to a small trial
- Optionally a follow-up: building that trial or a deeper session
Our promise
Your software stays yours
- Full code ownership The full source code is and stays yours, documented and ready to hand over.
- No vendor lock-in Stop working with us and your system keeps running. Any developer can pick it up.
- Fixed price up front You get a no-obligation blueprint and quote up front: no open-ended billing and no surprises afterwards.
- Security in every layer We build security-by-design, with a specialist in-house.
Frequently asked questions
What does an AI training or talk cost?
It depends on the format and the group. A half-day talk is a different thing from a hands-on workshop for a whole team, or a series of sessions per department. We always agree the price upfront, with no open end. In a short conversation we work out what fits: who's joining, which use cases are on the table, and whether you want one session or a track. After that you know exactly where you stand.
How long is a session and what does it look like?
A good session usually runs a half day: the basics briefly, then mostly doing it yourself. We start with a demo on real examples, then your team gets stuck in to OpenAI and Claude on your own tasks. We close with the do's and don'ts and a shortlist of use cases. We agree the programme in advance, so the time goes to your work rather than to general theory.
Will this training replace my people, or help them work better?
The goal is to make your people work better, not to replace them. We show where AI takes over the dull part of a task, freeing up time for the work that needs judgement. That's exactly how we use it ourselves in Simply: the admin goes to the system, the person keeps the decision. A training makes your team self-sufficient at that, it doesn't make them redundant.
Is AI genuinely needed here, or are you selling hype?
We'll tell you straight when AI isn't the answer. For some tasks a plain tool or a fixed way of working is better, faster and cheaper, and you'll hear that from us. We build with AI ourselves where it genuinely saves time, for instance in Simply, but we don't bolt it onto a process to sound modern. A session with us is just as much about when you shouldn't use AI.
What does my team concretely keep after the session?
Three things. Working example prompts on your own tasks, so they can carry on the next week. A one-pager of do's and don'ts around GDPR and the AI Act, so nobody has to guess what's safe. And a shortlist of use cases that actually pay off. Not vague inspiration, but something you can start with on Monday.
What if we want to take it further into a real application after the training?
Then we build a small trial together on one of the use cases from the shortlist. A contained automation or application that lets you see whether it works before you invest big. If you'd rather bring more people along first, a follow-up session per department works well. You're tied to nothing: the training stands on its own, a follow-up is a choice.
Ready to build?
Book a no-obligation call — we'd love to think through the best approach with you.
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