In-product AI features
Scoping, measurement design, and kill criteria for AI features that need to defend themselves against churn and margin impact.
Broader tier · fractional leadership is the usual fit
Most mid-market SaaS companies arrived at 2026 with the same problem: they have an AI roadmap, a few features in production, a few pilots stuck in proof-of-concept, and no single executive who owns whether any of it is commercially working. This is the problem fractional leadership is designed for.
For SaaS, our usual engagement is Fractional Leadership. A founder takes the AI seat on a quarterly retainer, owns the roadmap, defends the investment case in your boardroom, and scorecard-builds the full-time CAIO who eventually replaces us. Transformation Programs are also common where a specific product surface (onboarding, support, pricing, analytics) needs to ship AI capability that clears a commercial bar.
We don't do AI-for-AI's-sake SaaS work. If the right call is to not ship the feature, we'll say so on the first call.
Scoping, measurement design, and kill criteria for AI features that need to defend themselves against churn and margin impact.
Tier-1 deflection, agent-assist, and knowledge-base intelligence scoped against contact-rate reduction, not call deflection vanity metrics.
Usage-based pricing modeling, AI-feature pricing, and cohort-based upgrade intelligence.
Alexandria deployed inside your organization: an in-house 170-agent platform your product, ops, finance and GTM teams use directly.
A senior operator in your AI seat on a quarterly retainer, plus the scorecard for the full-time hire who replaces us.
AI features shipped inside your product, with support workflows that hold your brand voice.
Where AI fits your roadmap, ranked by ROI, risk and time-to-value. A plan your board can interrogate.
Thirty minutes with the operator who would take your AI seat. Bring the roadmap question your board keeps asking.