Pricing strategy for AI SaaS · Pricing models · Software pricing

    Predictable revenue for AI productsproducts, agents, platforms, services

    We build your pricing model so that revenue scales with the value you deliver. Pricing for AI SaaS companies, from AI agent pricing to dynamic, usage-based plans.

    See the 4-month C.O.R.E. engagement →

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    VALUECREATEDVALUECAPTURED20-40%OF CREATED VALUEGOES UNPRICEDValue metricPackagingWillingness to pay

    +55%

    year-on-year revenue growth

    +33%

    lift in ARPU

    Delivered by our repricing work at OLX Group, then repeated across more than 50 monetization engagements.

    $199 · 48-hour turnaround

    Get your pricing torn down by an expert.

    Send your product URL. We run it through our 14-step playbook and send a private 6-page scorecard with your four highest-leverage fixes. No call required.

    Request my teardown

    The gap

    Your product moves with usage. Your pricing still charges by the seat.

    AI products deliver outcomes and carry variable cost. Most of them are still sold on a model built for software that cost nothing to run. That is where the margin goes.

    What we rebuild

    Pricing architecture

    Tiers, fences and list prices that hold up in front of a buyer, indexed to the value you deliver.

    Value metric

    One unit buyers can forecast and your margin can survive, instead of seats that ignore usage.

    Willingness to pay

    Van Westendorp and Gabor-Granger interviews across your real segments, not a survey of opinions.

    Where we come in

    Seven ways this usually starts.

    Move off feature-based or seat-based pricing onto models tied to usage or outcomes
    Define the value metric, the number that should actually be driving the price
    Set AI agent pricing so margin holds up as usage and compute cost scale
    Build hybrid and dynamic pricing models when no single metric can carry the whole structure
    Design pricing that rewards renewal and expansion, not just the first sale
    Layer in monetization through add-ons, once the core price is right
    Rebuild packaging and tiers around what customers actually value

    The C.O.R.E. Framework

    How we turn pricing into predictable revenue in 4 months.

    A rigorous, 4-phase monetization transformation backed by 78 empirical analytical models. Built for SaaS and AI leaders who need defensible math, requiring ~50 hours of client team collaboration across 16 weeks.

    1. C[01]

      Capture

      Week 1–418h your team

      Audit transaction logs, cohort economics, churn drivers, and revenue leakage.

    2. O[02]

      Optimize

      Week 5–88h your team

      Architect new packaging tiers, feature fences, value metrics, and expansion loops.

    3. R[03]

      Research

      Week 9–126h your team

      Measure empirical willingness-to-pay via Van Westendorp, Gabor-Granger, and price elasticity curves.

    4. E[04]

      Execute

      Week 13–1618h your team

      Implement customer migration paths, grandfathering policies, sales playbooks, and billing logic.

    Interactive roadmap

    Explore the Interactive C.O.R.E. Roadmap & 78 Data Artifacts →

    Click through every phase, model the revenue upside, and inspect each analysis we run.

    Open the roadmap

    Ready to price your AI product properly?

    One call, thirty minutes. If your pricing is already capturing the value you create, we will tell you on the call.

    • A read on where your current model is leaking revenue
    • The value metric we would price you on instead
    • The first change to make, and what it is worth