AI agents and internal tools, built to be checked.
Small teams move fast, so the work around the product (support, onboarding, CRM, internal dashboards, investor updates) gets held together with Zapier and a few prompts. Then an agent tells a customer something nobody approved, or an automation quietly stops, and nobody notices for a week.
Zapier
Consulting, at work.
We run 34 agents in 9 departments. Here's what watches them.
Our monitor uses no AI model. It reads the job database and checks plain rules, so it can't be talked out of a problem.
Sound familiar in a young company?
- Zaps nobody can map"We have dozens of zaps and nobody knows which ones matter."
- Unapproved answers"The support bot answered something we never approved."
- A CRM without its owner"Our CRM was set up by the first sales hire, who left."
- Hand-built investor updates"Investor updates mean pulling numbers by hand from four tools."
- Demo versus production"The agent demo worked. Production is another story."
For a team of five to fifty.
Multi-agent systems
Agents that draft, check and file, with review before anything leaves
Agent monitoring & debugging
Tests on real cases and rule-based alarms for agents already live
Automation rescue
An inventory of every zap and flow, with the fragile ones rebuilt
CRM cleanup & data sync
Duplicates merged, owners assigned, nothing overwritten
Owner dashboards
The metrics investors ask for, on one screen, updated daily
Private AI on your own hardware
Local models for work that shouldn't leave your machines
Feasibility studies
A kill criterion set before you spend on the build
Part-time tech lead
A technical partner on call while you hire
After an agent check-up.
- MondayYour support agent runs against a test set of real past tickets before every change.
- TuesdayA webhook stops. The rule fires on the second failed run and the right person gets a phone alert.
- WednesdayThe CRM has one owner per account.
- ThursdayInvestor numbers assemble themselves.
- FridayNobody is debugging at midnight.
Three things we built in-house.
- A multi-agent operating systemRules first, a model second, routing work by the cost of being wrong.
- Agent monitoring and testingOur router went to 12 of 12 correct, about a second each, once its thinking mode was turned off. We also caught a local model silently cutting a 5,149-token prompt to its default 2,048 and fixed it with a 16K window.
- A voice assistant you can interruptWith 31 interruption checks.
From technical founders.
Can you check an agent someone else built?
Yes. We'd start read-only: compare its transcripts with its job, build a test set from real cases, add rule-based checks and log its decisions. Then we fix what the tests find.
Who owns the code?
You do. It lives in your repositories and accounts from the first commit.
Is anything watching your agents? Let's check.
The first call is free. Bring the automation you're most nervous about.