Language models (LLM)
Understand and produce language – like ChatGPT. Ideal for texts, questions and summaries.
In everyday life and across whole industries, there are AI solutions today that genuinely save you work. This page shows what's already possible – explained plainly, without jargon.
See examplesA few examples of what you can ask and which data is used. Click an example – the explanation unfolds.
Take a photo of your fridge and the AI recognises the ingredients. It suggests fitting dishes – from quick to fancy. If something's missing, it tells you what you still need.
Give a few keywords about the occasion and the person. The AI turns them into a speech in your tone – serious or funny. You only polish the parts that matter to you.
A photo is enough and the AI spots typical problems like overwatering, too little light or pests. It explains the cause in plain words. And tells you exactly what to do.
The AI searches your internal manuals and docs in seconds. It gives the meaning of the code and the right steps. All without company knowledge leaving the building.
From satellite data, the AI reads the state of your fields over time. It shows where growth stalls or stress appears. So you can act precisely instead of treating everything the same.
You describe the rule in plain language. A service continuously checks the weather and triggers when it rains. The AI then reminds you automatically of your task.
“AI” isn't one thing but many. Here are the key building blocks in plain words.
Understand and produce language – like ChatGPT. Ideal for texts, questions and summaries.
AI taps into your own knowledge – manuals, docs, data – and answers from it, without anything leaving the building.
AI that doesn't just answer but acts: plans, uses tools and works through steps on its own.
Make spatial data from sensors and satellites usable – from the map to the decision.
Fixed rules combined with AI – for example: “Remind me when it rains in Hamburg.”
Often a lean classification model solves the task more cheaply than a heavy image model. The right solution beats the biggest one.
They all handle the basics – the difference is in the peaks. A rough orientation, not a benchmark.
| Area | ChatGPTAll-rounder & images, large ecosystem | ClaudeAgentic work (Cowork) & code | GeminiGoogle integration, context & multimodal | Custom agents (e.g. Hermes)Tailored, cross-vendor model choice |
|---|---|---|---|---|
| Text & everyday | ✓ | ✓ | ✓ | ✓ |
| Programming / code | ★ | ★ | ✓ | ✓ |
| Image generation | ★ | – | ✓ | ✓ |
| Web research & current info | ✓ | ✓ | ★ | ✓ |
| Multimodal & large contexts | ✓ | ✓ | ★ | ✓ |
| Connect your own data (documents, company knowledge) | ✓ | ✓ | ✓ | ✓ |
| Combine different specialist AIs (image, voice, code) | ✓ | ✓ | ✓ | ★ |
| Cross-vendor model choice | – | – | – | ★ |
★ particular strength · ✓ good · – not the focus. “Custom agents” = individually built systems (e.g. Hermes): a freely chosen model, deeply integrated with your own data, tools and devices. Connecting documents & company knowledge is now possible on the big platforms too. For a single task, a custom agent is only as good as the AI it plugs in (e.g. image quality = the embedded image model like GPT Image, voices via services like ElevenLabs) – its own strength is combining several specialist AIs into one workflow. Model choice on the big platforms is only in-house (different GPT, Gemini or Claude models) – a custom agent chooses across vendors. General tendencies – models evolve quickly.
Take a real, small task from your day and try it with AI.
Say clearly what you need – spelled out, like to a colleague.
Often a simple tool is enough. More isn't automatically better.
AI can be wrong. The final look stays with you.
KIIDF is more than a name: behind this site stands a team of specialists in artificial intelligence, data and geoinformation, sharing their knowledge here in plain language.
For questions about AI systems, feel free to email us at: hello@kiidf.de