In 2026, the "AI agent" market splits into two camps. Generic tools (Tidio + GPT, Intercom Fin, Crisp + AI, ChatGPT custom) that bet on a well-prompted LLM. And vertical AI agents (Orkelia and a few competitors) built around a specific industry. Here's why the second wins on long-term retention.
1. The false promise of generic agents
Generic AI agents are seductive at demo: 30-40% sign-up conversion. Then month 3 comes. The agent suggests slots that don't exist in the calendar, gives approximate pricing based on "what GPT thinks is common", responds with vocabulary that doesn't fit the trade, and escalates at the wrong moments.
Empirical result: 60% of generic AI agent customers unsubscribe within the first 6 months. Not from bad faith — from wear. The agent does 80% of its job, but the remaining 20% are vertical-specific situations where it systematically derails.
2. What a vertical agent does differently
A vertical AI agent isn't "GPT with a prompt". It's a system including:
- Trade vocabulary integrated
- Native integrations (Doctolib, Combo, WhatsApp Business API)
- Pre-built escalation rules
- Contextual guardrails (never invents a price not in the database)
- Tone calibrated per client
3. Managed delivery — the real difference
| Dimension | Generic agent | Managed vertical |
|---|---|---|
| Initial setup | Self-serve | Pre-configured by trade expert |
| Maintenance | You handle | Included (auto industry updates) |
| Compliance | You manage GDPR/DPA | Included in service |
4. The Day-90 test
Simple test before signing: list 10 sensitive trade situations, send them as demo to each vendor. Generic: 4-5/10 handled correctly. Vertical: 8-9/10. That 5-point gap determines your 6-month retention.
5. Decision framework
3 questions: trade-specific vocabulary? time to maintain? conversation impacts revenue directly? 3 yes = managed vertical. 0 yes = generic suffices.
Explore the 6 Orkelia verticals or book 30 min to apply this to your case.
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