Questions 1–4: how they start
How a partner begins tells you how they'll finish.
- 1. Do you map our workflows before quoting, or quote from a call? (Diagnosis before prescription — anything else is guessing with your money)
- 2. What would make you tell us NOT to automate something? (A partner with no disqualification criteria is a vendor, not an advisor)
- 3. Which workflow would you automate first, and why that one? (Listen for volume, pain, and measurability — not whatever's trendy)
- 4. What do you need from our team, and how many hours? (Honest answers here predict honest timelines later)
Questions 5–8: how it runs
Production is where demos go to die. These four separate the survivors.
- 5. What happens when the agent hits a case it can't handle? (You want a designed exception path with human review, not 'the model is very good')
- 6. Can leadership see an audit trail of every action? (If not, it will fail its first executive question)
- 7. How do you test before production? (Real historical data, edge cases, stress tests — not a happy-path demo)
- 8. What breaks when our systems change, and who fixes it? (Systems live in changing environments; maintenance posture matters)
Questions 9–12: what you own
The difference between an asset and a hostage situation.
- 9. Who owns the code and the prompts? (The only acceptable answer: you do, outright)
- 10. Can we run it without you? (Yes should be immediate — with a handover plan)
- 11. What's the model dependency? (The foundation model should be a swappable component, not a lock-in)
- 12. Show me a system that's been in production over a year. (Operating history is the credential; demos age in weeks)
How we answer them
For transparency: we diagnose before we build (paid discovery that maps every system and handoff), we design exception paths and audit trails into every build, clients own 100% of the code with the model as a swappable component, and our systems run daily operations across finance, logistics, real estate, and SaaS — some for years. We've eliminated over 50,000 hours of manual work that way.
The fastest way to evaluate any partner — including us — is to bring a real workflow and watch how they think about it. Book a conversation, bring your messiest process, and ask all twelve.
Frequently asked questions
What should I look for in an AI automation company?
Five predictors: they diagnose before quoting, they design for exceptions (human-in-the-loop paths), every action is auditable, you own the code outright with no platform lock-in, and they can show systems that have run in production for a year or more.
What are red flags when hiring an AI vendor?
Quoting without mapping your workflows, no answer for exception handling, no audit trail, retained code ownership or proprietary-platform lock-in, and a portfolio of demos rather than operating systems. Aggressive certainty ('AI can automate anything') is itself a red flag.
Should we run a pilot before committing to a big program?
Yes — but a production pilot, not a sandbox demo. A tightly scoped first system on a real, high-volume workflow proves ROI and reveals how the partner operates. A demo on synthetic data proves nothing about production.