Predicate AI · Go-to-market · Senior · 45 to 60 minutes

How should Predicate price at launch?

Predicate AI builds AI software for legal work, including an AI native deposition tool. Answer this product management case and get it graded line by line against a weighted rubric.

pricing strategy
unit economics
go-to-market
executive communication
judgment under uncertainty

The situation

Predicate AI is preparing to launch an AI native deposition tool. The pricing lead has ten days to present a launch pricing strategy to the board, and asks you, the senior PM closest to the product, to help frame the recommendation. A small set of beta partners is waiting for commercial terms so they can decide whether to continue, expand, or become early references. Because the tool is new, there is little direct market data on willingness to pay, and standard SaaS heuristics may break if inference cost becomes a meaningful part of cost to serve. The team also needs a structure that sales can explain simply, finance can model, and customers will see as fair as their usage grows. The hard part is that a low friction entry price could speed adoption but lock in a weak anchor, while a more complex or usage linked model could better match value and cost but slow early deals. You need to recommend how Predicate should price at launch and how to handle beta partners without overfitting to them.

What to produce

A 2 page launch pricing memo for the board.

Your answer must

State one recommended launch pricing structure and the primary pricing metric.
Compare at least three plausible pricing options and reject the others with clear tradeoffs.
Show how inference cost affects your recommendation, including one safeguard if usage is heavier than expected.
Explain how beta partners should be handled at launch, including which concessions you would and would not offer.
Define the key unknowns, what you would measure in the first 90 days, and what would trigger a pricing review.
Assume any missing inputs you need and label them clearly.

Constraints

The board needs a recommendation in ten days.
Beta partners are already waiting for commercial terms.
You do not have direct historical pricing data for this product.
Inference cost must be treated as part of launch economics.

Format

Use five short sections, recommendation, options considered, economics, beta partner plan, risks and next steps.

How Predicate AI actually played it

A teaching case where a pricing lead for an AI deposition tool must present a launch pricing strategy to the board in ten days while beta partners wait. It works through cost items, value and which pricing structure to choose for a new AI product.

Treat inference cost as a real input to launch pricing
Beta partners create a deadline and a reference point
Choose a structure that scales with customer value

Built from Predicate AI: Pricing an AI-Native Deposition Tool at Launch by The Pricing Conundrum.