AI consulting services vs building an in-house ML team - what’s more cost-effective?

Our board is pushing us to integrate a custom predictive model into our core platform by the end of Q3, and I’m currently losing sleep over the budget. We are at a crossroads where we need to decide whether to burn our runway on hiring full-time engineers or to outsource the heavy lifting to external specialists. The ""talent war"" is making it nearly impossible to find decent ML talent without offering a king's ransom, so I’m seriously looking into ai consulting services as a potential shortcut.

Scaling an internal team feels like a safer long-term play for IP retention, but the overhead of benefits, equity, and onboarding is daunting. On the other hand, bringing in an agency might get us to an MVP faster, though I’ve heard horror stories about ""black box"" solutions that are impossible to maintain once the contract ends. We need a high-performing model for churn prediction, and we need it yesterday.

And here is what I am interested in:

- Have you found that ai consulting services actually save money in the long run, or do the hourly rates eventually exceed a full-time salary?

- What are the biggest red flags to look for when vetting an external AI agency?

- How do you handle the hand-off process to ensure your internal devs can actually manage the model later?

- Is it better to hire one ""Unicorn"" lead and let them build the team, or just outsource the entire initial build?

- Does the ""consulting"" route usually lead to generic solutions, or can they actually handle niche, proprietary data sets well?

- What’s the average timeline difference you’ve seen between an agency build and an in-house project?

I really need to figure out which path keeps our burn rate under control while still delivering a product that doesn't hallucinate. If you’ve been through this build-vs-buy battle recently, I’d appreciate some real talk.