Fencing the data
If you do not explicitly protect your inputs in the vendor contract, you have surrendered them. We mandate absolute data quarantine.
When an enterprise integrates a third-party AI model, the default terms often grant the vendor quiet access to proprietary data. We negotiate enterprise-grade procurement agreements that explicitly quarantine your data from public training sets, allocate liability for algorithmic hallucinations, and secure rigorous IP indemnification. We treat every API integration as an intellectual property transaction.
Every engagement is composed against these commitments. They shape the protections we add, the questions we ask, and the document that leaves the file.
If you do not explicitly protect your inputs in the vendor contract, you have surrendered them. We mandate absolute data quarantine.
When the model errs, liability must be apportioned. We draft the indemnities that protect the enterprise from third-party output claims.
Compute is a utility. We negotiate rigorous uptime guarantees and compute availability clauses to ensure the model functions at scale.
These are the terms, structures, and practical risks that usually decide whether the work holds when the file is tested.
Drafting strict zero-retention and zero-training covenants to ensure enterprise inputs are never used to improve the vendor's foundational models.
Structuring terms to ensure the enterprise retains exclusive ownership of all generated outputs, even when underlying model weights are proprietary.
Negotiating robust, uncapped indemnities from the vendor against claims that the model's outputs or training data infringe third-party IP.
Each step is concrete; each step has a deliverable. The scope is defined, the matter moves, and the file closes.
We dissect the vendor's standard enterprise agreement to expose data retention rights and liability disclaimers.
We aggressively negotiate the insertion of custom data quarantine provisions, output ownership clauses, and strict SLA requirements.
We mandate IP infringement indemnification, shifting the risk of training-data copyright violations back to the model provider.
We establish internal usage policies that align employee interaction with the finalized vendor terms.
These adjacent matters sit in the same transactional register. The scope changes; the posture stays procedural.
Secure defensible ownership, authorship posture, and output-rights terms when the model and its outputs become valuable IP.
Open the matterTranslate procurement risk into board oversight, reporting channels, and liability allocation before deployment scales.
Open the matterNegotiate the vendor agreements and indemnities required to safely deploy AI models at scale.
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