License without opening your training set.
Turn unpriced exposure into a per-output cost you can forecast. Yodal's architecture is designed to prove licensing compliance without disclosing training data.
- Litigation exposure is unbounded and unpriceable.
- Bilateral deals are lump sums unlinked to actual output.
- Any audit mechanism exposes training data to the auditor.
- Regulatory direction points toward per-use accounting.
- Per-output cost turns liability into a forecastable line item.
- Payment is proportional to measured contribution.
- Designed to run inside a TEE — training data never leaves the enclave.
- Audit trail without disclosure: the enclave attests, not reveals.
The integration
Designed for sealed inputs and auditable outputs.
How it works
Deploy the enclave
Yodal's attribution module is designed to run inside a trusted execution environment.
Route generations
Each output passes through the enclave. Measured contribution events are logged; training data is never exported.
License and attest
When a rightsholder's work likely contributed, the enclave records the event. If the publisher's terms are met, the license executes automatically.
We will never
Export training data
The enclave attests to contribution without revealing what was trained. Your data stays yours.
Set license prices
Publishers set terms. You see the rate before you opt in. Yodal measures and executes — nothing more.
Take a side
No models. No content. No consumer product. We're neutral by construction.
Talk to us
See what per-output licensing looks like for your stack. We'll walk you through the integration architecture and answer technical questions.
Or email us at pilot@yodal.ai