The real cost of building in-house
Two senior AI engineers plus a product owner is $500K+/year fully loaded — in a market where this talent is scarce and heavily recruited. Add three to six months of hiring, then months of learning your domain, then the unglamorous work: integrations, guardrails, exception handling, monitoring. Most first in-house systems ship in quarter three or four, if the team survives attrition.
That investment is justified when the AI system IS the product, or when a decade of proprietary-data advantage is at stake. It rarely is for operational automation.
What a specialist agency actually sells
Not headcount — pattern recognition. A firm that has shipped document pipelines, revenue engines, and voice agents across finance, healthcare, logistics, and SaaS has already made the expensive mistakes: which guardrails matter, where models fail, how to integrate with a 15-year-old ERP nobody documents. You're compressing a year of learning into weeks of discovery.
The vendor's job is also to make itself optional: everything we build is custom code the client owns outright — no per-seat license, no platform lock-in, and your team can take over operations whenever you're ready.
The hybrid model that usually wins
The pattern we see succeed: an agency designs and ships the first production systems and runs them while your one internal owner — an ops-minded engineer or technical PM — learns alongside. By system three or four, your team runs day-to-day operations and the agency drops to an advisory or expansion role. You get speed now and capability later, without the $500K/year bet.
Questions that expose a weak vendor
Whoever you evaluate — including us — ask:
- Do you start with a paid discovery that maps our workflows, or jump straight to a build quote? (Guessing is a red flag)
- What happens when the agent hits a case it can't handle? (No exception-handling answer = not production-grade)
- Can leadership see an audit trail of every action? (If not, it's a demo, not infrastructure)
- Who owns the code and can we run it without you? (Anything but 'you, and yes' is lock-in)
- Which of your systems have run in production for over a year? (Demos age fast; operations are the proof)
Frequently asked questions
Should we build AI automation in-house or hire an agency?
Build in-house when AI is your core product or long-term proprietary advantage — expect $400K–$700K/year for a minimal team and two to four quarters to first production. Hire a specialist when AI is how you improve operations: production systems ship in 4–10 weeks for a fraction of one year of in-house cost, and a hybrid handover builds internal capability afterward.
What should I look for in an AI automation agency?
Diagnosis before building (paid discovery that maps your workflows), production references older than a year, explicit exception-handling and human-in-the-loop design, leadership-visible audit trails, and full client ownership of the code with no platform lock-in.
Do we keep ownership of what the agency builds?
With the right contract, yes — insist on it. Everything Spiga Consulting builds is owned 100% by the client: custom code on your infrastructure, with the foundation model as a swappable component. You can operate it without us.