Software companies
Design partner agreements for AI features: data rights to settle up front
By SourceX Editorial · Reviewed by Noah Loul ·
Short answer
A design partner agreement for AI features should settle, before any data moves, which customer records you may use, which models may learn from them, who owns feedback and outputs, and what is deleted at exit. The rule of thumb: if a use is not named in the agreement, assume you need fresh written consent.
Key takeaways
- Name the systems and record types the partner shares; a general customer data clause invites disputes later.
- Treat partner-only models and shared models as separate permissions, and cover what third-party model providers may retain.
- Keep the feedback clause about product ideas, with an explicit carve-out for the partner's records.
- Agree at signing what happens to fine-tuned adapters, embeddings and evaluation sets when the partnership ends.
- Licensing a partner's records to any other company needs its own explicit consent, not a design partner clause.
Why data rights belong in the design partner agreement itself#
Data rights belong in the design partner agreement because the early AI build is when customer records are most likely to be copied into prompts, fine-tuning sets and evaluation suites. Once those copies exist, a later amendment cannot easily pull them back.
Changing terms after the fact also carries regulatory risk. In February 2024, FTC staff warned that a company adopting more permissive data practices, such as using consumers' data for AI training, and disclosing that only through a surreptitious, retroactive change to its terms or privacy policy may be engaging in unfair or deceptive practices. Design partners are usually businesses, but the lesson carries over: settle consent up front, in plain words.
A short data rights schedule attached to the agreement does more than a long general clause. It gives engineers a list they can follow and gives the partner's counsel something concrete to approve.
Clause checklist for AI design partner agreements#
The clause checklist below covers the decisions that most often go unanswered in pilot, beta and early access agreements. Each row is a question the agreement should answer in writing, with a common starting position you can adapt with counsel.
| Clause | Question it answers | Common starting position |
|---|---|---|
| Data scope | Which systems and record types the partner shares | A named list, such as support tickets, help center articles and usage logs |
| Model scope | Which models may be trained, tuned or evaluated | Use limited to the partner's own instance unless it opts in to shared models |
| Third-party providers | Whether model vendors may retain or train on inputs | Providers bound by no-training and deletion commitments |
| Outputs | Who owns generated drafts, labels and summaries | Partner owns outputs about its business; vendor keeps rights in the product |
| Feedback | What the vendor may do with suggestions | License to use product feedback, excluding the partner's records |
| Evaluation sets | Whether partner records may become test cases | Allowed during the program; deleted or de-identified at exit as agreed |
| Privacy and confidentiality | How personal and confidential details are handled | Data processing terms plus redaction rules for any training copy |
| Exit and deletion | What is deleted, retained or retrained at the end | A named deletion list with a written certificate |
| Onward licensing | Whether records can reach any other company | Prohibited without separate written consent |
- 01Your work records
- 02Personal details removed
- 03You approve the release
- 04Licensed to AI developers
How to define data scope#
Data scope is defined best by system and record type, not by the phrase customer data. A partner that agrees to share Zendesk tickets and help center articles has not agreed to share call recordings, Salesforce notes or Slack exports, and the agreement should say so.
Include the date range, the fields that are excluded and who performs the export. Many partners prefer to export a filtered set themselves rather than grant API access, which also leaves them with their own record of exactly what left their systems.
Model scope: the clause most teams leave vague#
Model scope states which models can learn from the partner's records, and it is the clause most often left vague. There is a real difference between using records to configure the partner's workspace, fine-tuning an adapter that only that partner uses, and improving a shared model that every customer receives.
Write each tier as a separate permission the partner can grant or refuse. Also cover the model providers in your stack: if a hosted model vendor processes the partner's records, the agreement should say whether that vendor may retain inputs or use them for its own training, and point to the terms that bind it.
Feedback, outputs and evaluation sets#
Feedback clauses are written for product ideas, and they cause trouble when they are read to cover the partner's records. A standard clause granting a broad license to use feedback should carve out customer data, prompts and uploaded documents, so nobody argues later that a batch of tickets counted as feedback.
Outputs and evaluation sets need their own lines. Evaluation sets built from a partner's real cases stay useful to the vendor long after the program, so decide whether they are deleted at exit, kept only in de-identified form, or kept with the partner's written permission.
Fill-in fields for your data rights schedule#
A data rights schedule can be added to an existing design partner or early access agreement as an exhibit. The fields below are the minimum to complete before signing; adapt the wording with counsel so it fits the main agreement's definitions.
- Systems in scope, for example Zendesk, Jira, Salesforce or a shared document folder.
- Record types in scope and record types excluded.
- Date range of records and who performs the export.
- Permitted uses: configuration, partner-only fine-tuning, shared model improvement, evaluation.
- Model providers that may process records, with their retention and training terms.
- Ownership of outputs, labels and evaluation results.
- Feedback license with a carve-out for customer records.
- Redaction rules for personal and confidential details before any training copy is made.
- Exit triggers, the deletion list, any retained items and the deletion certificate.
- Onward licensing: prohibited unless a separate written consent is signed.
Illustrative: a scheduling vendor and three design partners#
Illustrative: a fictional field scheduling software company invites three customers to test an AI dispatch assistant. Each partner shares job records, technician notes and customer messages from its own account.
The data rights schedule limits use to each partner's own instance by default. One partner opts in to shared model improvement after reviewing the redaction rules; the other two decline. The feedback clause excludes job records, and evaluation sets are kept only for the partner that consents in writing.
When one partner leaves the program, the vendor deletes its prompts, its partner-only adapter and its evaluation cases, then sends a deletion certificate. Because the schedule named each item, the exit is a checklist exercise rather than a negotiation.
How SourceX treats design partner records#
SourceX treats records that a design partner shared with a software company as customer-controlled, so they are excluded from any licensing package by default. A design partner agreement that permits product improvement does not, on its own, permit licensing those records to an AI developer.
When a software company wants to license its own operational records, such as engineering issues, code reviews and internal support workflows, the Rights step of the SourceX five-step transaction separates company-owned records from customer content. The SourceX Evidence Packet then records permitted use and release authorization for what remains.
Frequently asked questions
Is a design partner agreement the same as a beta or pilot agreement?
They overlap. Beta and pilot agreements usually focus on access, fees, warranties and confidentiality, while a design partner agreement adds a closer working relationship and more structured feedback. For AI features, any of them needs the same data rights schedule, because the risk comes from the records shared, not the program name.
Can we rely on our standard terms of service instead?
Standard terms rarely describe AI uses in enough detail, and many enterprise customers negotiate them away. A short schedule tied to the design partner program is easier for a partner's counsel to approve and gives your team clear operating rules. Review existing terms with counsel so the schedule and the main agreement do not conflict.
What if a partner wants its data removed from a model already trained?
Removing one partner's influence from shared model weights is often impractical, which is why shared training should be an explicit opt-in. For partner-only models or adapters, deletion is straightforward. State in the agreement which artifacts are deleted, which are retrained and what confirmation the partner receives.
Should design partners be compensated for data use?
That is a commercial choice. Many vendors offer early access or pricing benefits in exchange for feedback, but a benefit does not replace clear consent for specific uses. If you tie a benefit to shared model training, describe the use plainly so the partner knows exactly what it is agreeing to.
Do these rules apply to internal dogfooding?
Internal use of your own company records is a different question, since the company controls them. Rights still matter if internal records contain customer content, such as tickets, attachments or screenshots. Separate company-owned records from customer content before using either for training.
Sources
- On February 13, 2024, FTC staff warned that a company that adopts more permissive data practices, such as using consumers' data for AI training, and tells consumers only through a surreptitious, retroactive change to its terms of service or privacy policy may be engaging in unfair or deceptive practices. Source
Related resources
- QuestionShould companies sell or license their data?
- InsightSharing data licensing revenue with customers: a model for vertical SaaS
- DataSales call transcripts
- GlossaryRevenue share
- QuestionData licensing vs data selling: what's the difference?
- InsightCan fitness and wellness businesses sell their data to AI companies?
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