Developing a pricing model is one of the most nerve-wracking decisions an early-stage founder will face, especially in the world of B2B AI SaaS pricing. Get it wrong, and you may miss your market. Get it right, and pricing can become a growth accelerant and strategic advantage. But where do you start?

As an early AI SaaS company, you’re probably trying to do something novel. That means you’re often operating in whitespace: no obvious comps, few standard benchmarks, and a product whose value may shift radically depending on the use case or the user.

On top of that, AI products introduce a new wrinkle: variable cost structures. Unlike traditional SaaS, inference costs (e.g., compute tokens or API calls) can create unpredictable margins and pricing constraints that change as your customer grows. This means pricing is a risk management strategy as much as it is a monetization lever.

After conducting interviews with dozens of early-stage operators and studying frameworks from leading SaaS thinkers, we built a decision tree to help founders think through their initial pricing strategy. This tool isn't designed to give you a final answer, but rather kickstart the right conversations.

The Three Main Pricing Components

To navigate your earliest pricing decision-making, there are three major pricing building blocks:

Free: To freemium, or not to freemium?

Should you offer a free version? Ask yourself whether it’s standard in your category, whether non-paying users are monetizable, and whether your cost to serve them is low enough. If not, a freemium play might do more harm than good.

Base: Platform fee vs. per-user subscription?

Is most of your value tied to variable usage, or is access itself valuable? This distinction helps determine if you should anchor pricing around a flat platform fee, per-user license or tiered subscription model.

Variable by Action: Should pricing scale with use or value?

Are success metrics clearly quantifiable? Does your cost structure scale with volume or user activity? If so, layering in variable fees (based on usage, performance or outcomes) might make sense.

As you and your team work through these flows, it is important to keep in mind:

• You may not need free, base and variable components to your pricing
• Be as data-driven as possible to anchor pricing discussions on value provided
• Per-seat or per-user pricing makes the most sense where the product enhances human performance vs. replaces it
• While usage-based pricing allows vendors to recoup costs, it can can create frustrating customer experiences via:
  • Ongoing purchasing decisions
  • Harder capacity planning/budgeting
  • ‘Surprise’ spikey invoices
• Usage-based pricing can be a better fit when there are consistent, predictable workloads
• Ensure success metrics don’t create misaligned incentives. For example, if AI agents are evaluated on resolution speed, they may compromise resolution quality
• You never want to have to debate what a “successful” outcome is with the customer

Spark Healthy Debate

This framework is meant to open up a healthy dialogue – internally and with your advisors – about how pricing relates to value, cost and customer behavior. By design, it’s not a perfect algorithm. Every early-stage product has edge cases, nuance and strategic trade-offs that a rigid model can’t capture.

Some of the best pricing strategies are born from structured experimentation. If a freemium test helps you learn about acquisition, great. If a usage-based model improves LTV but causes customer frustration, that’s worth fixing early.

At minimum, you want your pricing strategy to:

• Reflect your value proposition
• Align with how customers experience success
• Scale sustainably as usage grows

With Pricing Set, the Real Fun Begins

Talented founders are acutely aware that deciding on an initial pricing model is just the beginning.

Ronak Gandhi, cofounder of Structify, can attest that picking a pricing structure was just the start. The "highest-stress point" was organizing the pricing card on their webpage – determining the right language and how features should align at each pricing tier. Then, the next challenge was identifying key post-launch metrics to determine whether the pricing strategy was resonating.

The only certainty: what you first go to market with will change over time – and it should. Invest in developing a thoughtful initial pricing strategy, but don’t stay married to it. Get the early logos. Be agile. Reacting to market feedback is always the recipe for success.

If you're an early-stage founder grappling with these questions, I’d love to be a thought partner. Whether you're debating freemium vs. paid trials, stuck on usage tiers or just looking for a second opinion, feel free to reach out to ncoletta@baincapital.com.