Most accounts start with one AI Agent. Many end up with two or three, each focused on a specific scenario. Multiple AI Agents are usually a better design than one trying to do everything.
When one is enough
Single property
A small set of guest channels (one or two)
Knowledge needs are similar across all channels (check-in, parking, breakfast, and so on)
Keep it simple. Add a second AI Agent only when the first one cannot do the job well.
When to add a second
Several patterns justify splitting:
Different channels with different needs. A WhatsApp-only check-in AI Agent can have a different tone, shorter responses, and a tighter knowledge section than an email reservations AI Agent.
Different properties. Each property has its own Facts (address, hours, parking), so giving each property a dedicated AI Agent keeps the knowledge clean.
Different teams behind the handovers. If WhatsApp handovers should go to the front desk and email handovers to reservations, splitting aligns with the handover routing.
Knowledge is per AI Agent
Each AI Agent has its own knowledge section. There is no shared knowledge pool. If you run two AI Agents, each maintains its own Facts and FAQs.
This is intentional. It lets each AI Agent stay tightly scoped to its use case. The tradeoff is that shared topics (cancellation policy, breakfast hours) need to be maintained in each agent that handles them.
If you find yourself updating the same Fact across many agents, consider whether the Property Assistant template's clone-per-property pattern fits, or whether a single broader AI Agent would serve you better.
How most teams structure it
The most common pattern in early-release accounts: one arrival/check-in AI Agent on WhatsApp, plus one general enquiries AI Agent on email. Two AI Agents, clear scopes, and manageable knowledge maintenance.
Need Help?
Please contact us through the 'Talk to Us' option on the left menu in the platform, or through the Bookboost Support email at support@bookboost.io if you have questions or need additional support.