The most common question before an AI project: 'isn't ChatGPT enough?' Short answer — for your team's daily work, yes; for a customer-facing, data-bound product, no. Here is the honest breakdown.
It doesn't. The public model knows nothing about your internal documents, prices, or customers. Only a RAG system connects the model to your private data — with citations, kept current.
Works for a few pages. With thousands of documents it won't fit the context window, it's expensive, and there's no source tracking. That's when you need retrieval (RAG) and evaluation.
For individual use, yes. But you can't serve a customer-facing product through 30 people sharing a ChatGPT account — you need an API, an application layer, controls. They are different things.
Start with a ChatGPT/Claude Team subscription for your team's daily work — it pays for itself immediately. Build a custom system only when there's a customer-facing, data-bound, or integrated use-case. The two don't compete: most companies need both, for different jobs.
A 30-minute call to scope the use-case — if ChatGPT is enough, we'll say so.
Book a discovery call| Custom AI system | ChatGPT subscription | |
|---|---|---|
| Answers from your private data (RAG) | ||
| Integration with CRM / ERP / e-commerce | ||
| Customer-facing surface (chatbot, product) | ||
| Audit trail and GDPR / DORA compliance | Limited | |
| Guaranteed accuracy (eval suite) | ||
| Individual team productivity | Overkill for it | |
| Instant start | 4–8 weeks | Same day |
| Cost | €15k+ to build | €25–€30/user/mo |
Engagement tiers
Fixed prices. 100% IP yours. Most clients start with a 30-min scoping call so we agree on the right tier before any building.
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30-minute discovery call, fixed-price quote, 4-week roadmap. The next project could be yours.
Real reviews
Quick feedback from people who worked with our team.
Overall
Based on real reviews
I stopped guessing. Now I follow clear steps and get solid results every time.
Now I know what to ask and how to get clean outputs for posts, emails, and offers.
They quickly identified what to automate, what to tighten up, and how to structure the system better.
New reviews get added regularly.
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