From training data to model weights, protect your AI intellectual property with NDAs designed for the unique complexities of machine learning. Derivative works, bias provisions, and responsible AI clauses included.
Specialized confidentiality agreements for every AI development scenario
Protect datasets shared for model training. Covers data provenance, permitted uses, derivative works, and bias representations.
Generate Template →Secure model weights, architectures, and hyperparameters. Prevents reverse engineering, distillation, and unauthorized fine-tuning.
Generate Template →For joint AI development, research collaborations, and technology partnerships. Clear IP ownership and contribution tracking.
Generate Template →Protect confidential terms when licensing datasets. Covers pricing, usage restrictions, and exclusivity arrangements.
Generate Template →Responsible AI clauses for bias testing, prohibited uses, transparency requirements, and human oversight obligations.
View Provisions →Create a fully customized AI/ML NDA with our interactive generator and AI-specific clause library.
Start Building →Standard business NDAs miss critical AI-specific concerns
AI NDAs must address data provenance, licensing chains, and whether trained models constitute derivative works of the underlying data.
Weights, architectures, and hyperparameters need specific protections. Standard trade secret language often fails to cover model distillation or fine-tuning.
When models are fine-tuned or adapted, who owns the derivative? AI NDAs need clear rules for model improvements and adaptations.
Address who is responsible when AI systems produce biased outputs. Ethical use provisions and prohibited applications must be specified.
Protect against model extraction attacks, API probing, and attempts to recreate proprietary systems through output analysis.
Balance confidentiality with emerging AI transparency regulations. Define what can be disclosed for audits and compliance.
AI-specific clauses built into each NDA
Require disclosure of data sources, licensing chains, and any known biases or limitations in training data.
Clear ownership rules for base models, fine-tuned variants, and improvements developed during the relationship.
Prevent model distillation, knowledge extraction, and attempts to recreate proprietary systems.
Define off-limits applications like weapons, mass surveillance, or discriminatory decision-making.
Require human review for high-stakes decisions and maintain meaningful human control over AI systems.
Preserve rights to audit AI systems for bias, safety, and compliance while protecting confidential information.
Explore NDA templates for other specialized industries