Pay for what you use, not for the seats you fill.
Per-seat pricing made sense when every agent needed a dedicated licence. The product has changed. The pricing model should too.
An analysis of how consumption pricing changes the math as your team grows.
On BootDesk consumption pricing, the same team pays a floor and a metered overage. Add ten agents, the floor does not move. They only cost something when they do work that consumes model tokens, active channels, or other metered resources.
Growing teams face a choice: add headcount and absorb the per-seat cost, or keep the team lean and risk burnout. Consumption pricing removes that trade-off. The tool scales with the work, not the team size.
Quiet months cost less. Busy months cost the floor plus usage. The bill tracks reality instead of an arbitrary headcount.
How the math changes.
A thirty-person team on a per-seat helpdesk pays roughly €2,500–3,500 per month before add-ons. On BootDesk consumption pricing, the same team pays a floor and a metered overage.
What you pay for
BootDesk meter
four resources01
metered
Model tokens
The words the assistant reads and writes. Priced per million tokens.
02
metered
Active channels
A channel counts as active when it carries at least one conversation in the month.
03
metered
Image generation
Pictures the assistant produces for replies and campaigns.
04
metered
Users
Teammates who signed in to the workspace. The agent on holiday does not bill.
Quiet months cost less. Busy months cost the floor plus usage. The bill tracks reality instead of an arbitrary headcount.
Estimate your monthly bill
Pick a tier, set your usage, read the math. Defaults reflect a small team.
See the pricing page.
About the author
Written by the BootDesk team, the operators building BootDesk. We have answered tickets, owned SLAs, and trained agents.
More field notes. Read the next chapter.
Twelve channels, one ticket: what omnichannel actually looks like
The difference between having multiple channels and having one thread per customer. A field report from teams that made the switch.
6 minWhat we learned building an assistant that reads the full thread
Building an assistant that reads every message before it replies sounds obvious. Making it fast, accurate, and safe at scale took some lessons.
8 minRead the field guide. Try the product.
The field notes are draft chapters. The product ships today. Wire one channel, let the assistant answer the first ticket, read the statement at the end of the month.