White-label AI automation
White-label AI automation for client operations
We automate the repetitive work inside a client's business and leave your agency as the vendor of record.
Agencies are being asked for AI in proposals that are really about operations. Someone wants the inbox sorted, the CRM updated, the PDFs read, or the missed calls returned. White-label AI automation is how you sell that outcome without staffing a research group.
We start from the steps a person already takes. Which fields get copied, which decisions are reversible, and which ones would be costly if a model guessed. Anything that spends money, writes to a customer, or files a record keeps a human check until you have measured the error rate.
The system is branded as yours. Prompts, evaluation sets, and the runbook live in the client's workspace. If they leave, they take it with them. We do not rent a black box that stops when our invoice stops, unless a retainer is what you actually sold.
Deliverables
- Process map
- The current steps, plus an explicit list of actions the system is not allowed to take.
- Integrations
- Connections to the inbox, CRM, drive, phone system, or database already in use.
- Review queue
- A place for a person to approve customer-facing or financial actions.
- Evaluation set
- Real examples with names removed, so changes are judged on their work, not a demo.
- Operator runbook
- What to do on a Monday when a run fails, written for the client's staff.
Process
- 01
Collect samples
About twenty real items and the rule a senior person uses when the case is awkward.
- 02
Draw the boundary
What may run alone, and what may only draft for approval.
- 03
Connect with least privilege
Keys live in the client's account. We ask for the smallest scope that does the job.
- 04
Trial on live work
A short period where a person still approves every consequential action.
- 05
Leave a log
You can see what ran, what failed, and what a person changed.
Tech we use
- Model APIsChosen per job. The proposal does not lock the client to one lab.
- Ordinary codeRules and formatting stay deterministic where a model would be theater.
- Existing SaaS APIsWe write into the CRM they have, instead of selling them another one.
- Queue and logA failed run can be replayed. Silent failure is a defect.
- Voice only when neededA phone agent is a product. We scope it like one.
Questions agencies ask
Will you add a chatbot to their marketing site?
Only if that is the engagement. Most of the useful work is internal: sorting, drafting, filing, and routing. A public chatbot is a support product with its own scope.
Whose data is sent to a model?
The client's, under their API key, with a written note of what leaves their network. We do not paste their material into a personal chat account.
What happens when the model is wrong?
A person still has the last click on anything that matters. We keep the failures so the next change is based on those cases.
Can you repeat this for every client of a packaged offer?
Yes. If you sell a named service — a receptionist, a proposal desk, an intake lane — we build it once and stand it up per client with their keys and their brand.
If the client already said yes, send the brief.
Tell us what you sold, the date they expect, and whether we should stay off the call. We reply within one business day.