Multi-client automation platform
One environment, many clients, no shared blast radius.
shared platform
wa · +57 ···
- workflows
- credentials
- data
- failure domain
wa · +57 ···
- workflows
- credentials
- data
- failure domain
wa · +57 ···
- workflows
- credentials
- data
- failure domain
shared: the platform definition only. nothing else crosses a wall.
The problem
Running automation for several clients out of one shared environment is the fastest way to start and the fastest way to get hurt. Credentials sit next to each other. A workflow edited for one client runs for all of them. One rate limit, one bad deploy, or one noisy integration becomes everybody’s outage.
The alternative most studios land on is a separate hand-built setup per client, which trades one problem for another: nothing is consistent, nothing is reusable, and onboarding gets slower with every client added.
How a tenant is stood up
Give every client their own walls
Each client runs in an isolated environment with their own workflows, their own credentials, and their own data. Nothing is shared by default, so a change made for one client has no path to another.
Containerize the unit, not the client
The environment is defined once and provisioned per tenant with Docker. What each client gets is identical in shape and separate in state, which is what makes the setup reproducible rather than bespoke.
Separate the channel identities
Each client connects through their own Meta app and WhatsApp number, so messaging identity, rate limits and permissions belong to the client rather than to a shared pool.
Make onboarding a provisioning step
Adding a client is standing up a new tenant from a known-good definition, not rebuilding an integration from scratch. The cost of the tenth client looks like the cost of the second.
What it handles
Stack
Automation
- n8n
Channel
- Meta Apps
- WhatsApp Cloud API
Infrastructure
- Docker
Outcome
A change or a failure inside one client environment has no path into another. Onboarding a client is a provisioning step from a known-good definition rather than a rebuild, so the cost of the tenth looks like the cost of the second.
Next case study
Appointment automation