What's the cost difference between hiring a CTO and using fractional AI advisory?
Aegis scopes the CTO function as fractional-cadence delivery rather than a full-time hire. The agent layer handles recurring analysis between advisor sessions. Pricing is set after discovery.
The short answer.
Aegis scopes the CTO function as fractional-cadence delivery rather than a full-time hire. The agent layer handles recurring analysis between advisor sessions. Pricing is set after discovery.
This is a question Aegis hears regularly during discovery. Here is the practical way to frame it.
How Aegis approaches this.
Aegis Boardroom's answer is shaped by three frameworks. Truth Architecture: recommendations are designed to be source-traced. Confidence Contract: recommendations are mapped to the canonical Aegis confidence states (I Know / I Think / I'm Inferring / I Don't Know). Life Integrity Engine: recommendations that may increase irreversible-harm risk are flagged for refusal or human review, not softened.
The fastest path is the AI Readiness Assessment: it returns a confidence-mapped band for your specific situation. From there, the Quick Win Plan or a deeper engagement scopes the right paid Aegis next step.
Frequently asked questions.
Why is fractional AI advisory cheaper than a full-time CTO?
Because you're paying for the CTO function at a fractional cadence, not a full-time salary plus benefits and equity. An agent layer handles the recurring analysis between advisor sessions.
Can you just tell me the price?
Not before discovery. Pricing is set after we understand the scope, because quoting a number before knowing the work would be a guess.
What do I actually get between advisor sessions?
The agent layer handles the recurring analysis, so the work continues between sessions instead of stalling until the next meeting.