The market for AI chatbots is growing rapidly. With every new model generation, more platforms and more features emerge — along with more confusion. Today, companies face a fundamental decision: build themselves or have it built? Most well-known tools follow a do-it-yourself approach, where companies must configure and maintain their chatbot using no-code or low-code builders. That sounds attractive, but in reality it means ongoing effort.
At the same time, a second and fast-growing category is emerging: Managed AI. Instead of receiving a chatbot builder, companies get a finished, professionally maintained product that evolves continuously — without tying up internal resources. This difference impacts quality, maintenance workload, and long-term costs far more than many expect.
To provide clarity, the following offers a compact market overview of the most relevant providers and models.
DIY solutions like ChatGPT/GPTs, Botpress, Landbot, or Tidio allow a quick start but require companies to continuously update their knowledge base, flows, and content. Error analysis, optimization, and model updates are also fully their own responsibility. For teams with time and technical expertise, this can be a flexible solution — but for many others, it becomes a permanent technological construction site.
Managed-AI providers, on the other hand, operate completely differently: setup, data integration, continuous maintenance, quality control, and optimizations are all included. The result is less a software tool and more a sustainable AI service that works in the background and delivers measurable results — without requiring internal specialist knowledge.
| Provider | Category | Effort for the Customer | Best For |
|---|---|---|---|
| ChatGPT / GPTs | DIY | high – content, logic & maintenance done manually | experiments, small teams |
| Botpress | DIY | high – technical setup & training required | developer teams, complex workflows |
| Tidio / Landbot | DIY | medium – easy to start, but maintenance-heavy | marketing & website teams |
| Intercom (Fin AI) | Hybrid | medium – content & structure must be maintained internally | companies already using Intercom |
| Ada (Enterprise) | Managed | low – full service included | enterprise customers |
| livestep | Managed | very low – setup, maintenance & optimization included | companies seeking a fully managed, continuously improving system |
For many companies, the last few years have shown: the real effort of a chatbot begins after the launch. Content becomes outdated, product offerings change, internal processes evolve, and new model versions appear monthly. Reflecting these changes cleanly in a DIY bot requires more expertise and time than initially expected.
Managed AI solves this problem directly. Providers like livestep take care of setup, monitoring, quality control, analysis of user questions, and continuous optimization. Updates are part of the service, ensuring the chatbot stays consistent and reliable — without anyone internally having to become a “prompt engineer.”
The result: companies aren’t buying “software,” but a functioning system that delivers results.
Many companies start with a DIY builder and only later realize that maintenance, content management, optimization, and error analysis consume far more resources than expected. Those looking for a solution that works without internal teams and evolves continuously will achieve more stability and better long-term results with a managed-AI approach.
In a market that is changing so quickly, the difference between a self-built bot and a professionally managed AI system is becoming increasingly significant. In the end, the deciding factor is not the platform — but the effort you're willing to invest and the quality you expect.
