Enterprise buyers now send AI addendums, model risk questionnaires and supplier terms that ask questions your standard SaaS contract never answered. We negotiate enterprise MSAs, AI-use schedules and bank or financial institution supplier terms so you can close the deal without promising things your product cannot do. When requirements turn on regulation that applies to the customer, we say which ones and why.
At a glance
- Practice
- AI Infrastructure
- Pricing
- Flat fee, quoted before we start
- Included
- 6 deliverables
- Process
- 3 steps, one named attorney
- Where we work
- Slack, email or a call
When founders call us
The moments that usually bring a company to us for this work.
- 01
A bank sent a supplier agreement with model risk, audit and third-party oversight terms.
- 02
An enterprise customer attached an AI addendum demanding no training on its data and IP indemnity for outputs.
- 03
Your standard contract has no AI-specific terms and enterprise prospects keep asking for them.
- 04
Procurement wants uncapped liability for data incidents and you need a defensible position.
What you get
Scoped in writing before we start. One flat fee for all of it.
- Negotiation of enterprise MSAs and order forms for AI products
- AI-use schedule covering training on customer data, output ownership, human oversight and model changes
- Review of financial institution supplier terms, including audit, subcontractor and model risk requirements
- Positions on output IP indemnities, accuracy disclaimers and liability caps
- Security, DPA and data residency terms aligned with your actual architecture
- Reusable fallback positions and playbook for your sales team
How it works
- 1
Learn your product
We confirm how your system handles data, models and outputs so commitments match reality.
- 2
Negotiate the paper
We redline the customer's contract or your template and work through procurement.
- 3
Build the playbook
We turn the positions into a reusable guide for future enterprise deals.
Mistakes we help you avoid
The ones we see most often, and catch before they cost you.
- Avoided
Agreeing to an uncapped output IP indemnity without limits tied to your model providers' own commitments.
- Avoided
Promising no training on customer data when a subprocessor's terms do not match.
- Avoided
Accepting bank audit and subcontractor terms you cannot flow down to your cloud and model providers.
- Avoided
Committing to notify the customer of every model change, which you cannot practically do.
Enterprise AI Customer Contracts: questions founders ask
It is a schedule that adds AI-specific terms to a standard agreement. Common topics include training on customer data, ownership of outputs, transparency, human review and notice of model changes. Some customers send their own, and some vendors prefer to offer one proactively.
Many enterprise customers ask for one, and some vendors offer it with conditions. The key is scoping it: excluding customer inputs and modifications, capping it, and aligning it with any protection you get from your model providers. Your position depends on your product and your upstream terms.
Banks and other regulated financial institutions are expected by their regulators to oversee third-party risk, and many have model risk management requirements. That often means audit rights, subcontractor approval and detailed security obligations in supplier terms. We help you meet what is necessary without accepting more than the regulation calls for.
You can start with it, but it likely does not address training data, outputs, model changes or AI-specific risk. Adding a short AI schedule usually answers enterprise questions faster than negotiating them one deal at a time.
Get a flat-fee quote for Enterprise AI Customer Contracts.
A short call with an attorney. You leave with a written scope and one fixed price.
Book a call