AfterQuery shifting to outcome contracts

This pricing model turns AfterQuery from a data vendor into a specialized performance contractor. In the biggest deals, the buyer is not paying for a pile of labels or seats in software, it is paying to move a model from failing a real workflow to completing it reliably, whether that means coding in a terminal, handling a finance task, or executing a customer support flow. That naturally creates multi million dollar scopes, longer project cycles, and deeper embed with post training and eval teams.

• The workflow is consultative and concrete. Teams start with a capability gap, then AfterQuery defines the target task, builds or adapts the dataset, RL environment, and eval, and keeps expanding as results show up. That is much closer to paid model improvement work than to buying standard SaaS seats.
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• This is where AfterQuery differs from marketplace style providers. Invisible and similar vendors can price labor by the hour and split tasks across large workforces, while AfterQuery keeps more of the stack in house and custom builds tooling, which supports tighter quality control and lets custom projects produce reusable rubrics and environment templates.
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• The broader market is moving the same direction. Handshake, Mercor, Scale, Surge, and others are all trying to climb from interchangeable labor supply into stickier infrastructure like evals and RL environments. That is because the durable budget sits closest to measurable model improvement, not raw annotation volume.
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The next step is a split model. Custom outcome driven projects will keep winning the largest budgets, while the best pieces of those projects become repeatable products, like domain eval packs, environment templates, and benchmark suites. If AfterQuery keeps making that transition, it can turn one off wins into a compounding software and data layer around professional model work.