Your economics. One engine.

A scaleup's problem is sequencing: which growth lever gets the next dollar this quarter. The engine reads billing, pipeline, and product together, re-ranks the moves as results land, and keeps budget on whatever compounds ARR fastest. That holds at one million of ARR and at forty: hypergrowth is a state, not a size.

Most SaaS growth problems look like a traffic problem and turn out to be a payback problem. The engine reads billing, product, and pipeline together, so the ranked moves are the ones that change the unit economics rather than the top of the funnel. Which levers dominate depends on what the company sells: product-led motions live on trial design and seat expansion, sales-led motions on pricing power and win rate.

Firms that live on referrals have no way to price a growth decision, because the pipeline arrives without a source. The engine builds the missing attribution, then ranks the moves that add qualified enquiries without adding headcount.

Blended ROAS hides which products actually pay. The engine reads orders, costs, and spend together, so the ranked moves are scored on contribution margin instead of the number the ad platform reports.

Companies selling AI applications grow fast into an unsolved question: what a seat, a credit, or an outcome should cost when every answer carries an inference bill. The engine reads billing, usage, and model spend together, so pricing and packaging moves are scored on margin per account rather than on adoption alone.

For API-first and usage-priced products, growth lives inside existing accounts: metering, activation to production, net revenue retention. The engine reads consumption events against billing, so the ranked moves are the ones that turn usage growth into revenue growth.