Use waiser data to find documented synthetic datasets for AI testing, validation, demonstration and risk assessment — under licence terms that state what's allowed and what isn't, before you sign.
Each scenario keeps the existing dataset's licence posture in writing — so the question of "can we actually use this for that?" is answered before the project starts.
Pressure-test a customer-support assistant against thousands of plausible turns it has never seen — without sending a single real conversation back through prompt-engineering.
Licence posture
Testing and validation. Commercial use covered by the standard licence.
Drill privacy and consumer-rights workflows on synthetic subject access, deletion and rectification requests modelled on real regulatory patterns.
Licence posture
Validation and demonstration. Not for inferring identities of real individuals.
Probe model behaviour across demographic and linguistic axes with datasets built specifically to surface disparity — not as a side-effect of scraping.
Licence posture
Research, validation and red-team. Documented limitations attached.
Exercise fraud, AML and reconciliation pipelines on transaction flows that mirror real distributions without exposing real customer records.
Licence posture
Testing and validation. Permitted in production-equivalent environments.
Ship sales demos, sandboxes and customer trials with data that looks real, behaves real, and carries a licence cleared for external presentation.
Licence posture
Demonstration and commercial use. Redistribution restricted.
Run structured adversarial evaluations — jailbreaks, prompt injection, edge-case probing — against AI systems with datasets purpose-built for the exercise.
Licence posture
Research and red-team. Reviewer notes attached for sensitive scenarios.
Each role gets the same dossier — read at a different depth, used to answer a different question.
Need to ship features without waiting months for legal to clear training data. Use waiser to validate, benchmark and demo against documented sets.
Need a defensible answer to 'where did this data come from?' for every dataset feeding a production AI system. The dossier is built for that audience.
Run AI assessments and proofs of value for clients without exposing client data — and without inheriting somebody else's licensing problem.
Evaluate AI systems against documented inputs. Each dataset's dossier is the audit trail you would otherwise have to assemble yourself.
Build courses, certifications and labs on data students can actually use — with clear permission and stable versioning.
We'd rather be useful for a few real jobs than vaguely positioned for everything. If your need lives in this list, we'll tell you up front.
Start with the catalog if the use case is common; request a custom dataset if it isn't. Either way, you get the dossier before you commit.