Can Your Customers Rely on Your AI Coding Tool Indemnities? Pass-Through and Flow-Down Explained

Pass-through and flow-down: two different mechanisms

The terms are often used loosely, so it helps to separate them. Pass-through means extending a vendor's protection to a downstream party. That can happen through a direct right for your customers, through a commitment that you will enforce the vendor's indemnity on their behalf, or by drafting your own indemnity so that it mirrors what the vendor gives you. Flow-down means imposing obligations on downstream parties so that upstream conditions remain satisfied, for example requiring customers to keep a configuration unchanged, to give prompt notice of a claim, or to avoid modifying delivered code in ways the vendor excludes.

The practical consequence is that a vendor indemnity does not automatically reach your customers. In most supply arrangements it runs to the vendor's own customer, which is you. When you ship software and promise your customers IP protection, you are making a separate commitment backed by your own balance sheet. Whether the vendor's protection sits behind that commitment depends on the contract language, including any limits on transfer or on who may claim.

This guide is educational and is not legal advice. Pass-through and flow-down analysis should be reviewed by counsel against your actual agreements.

Where upstream and downstream terms diverge

Procurement teams usually review the vendor agreement and the customer agreement separately, and the gap appears when they are laid side by side. Vendor indemnities are commonly limited by covered products or plans, by which outputs are covered, by financial caps, by exclusions and by notice requirements. They may also depend on specific vendor safeguards, such as a public-code filter, remaining enabled. Your customer indemnity may be uncapped or carry a different cap, may cover the whole delivered product rather than selected outputs, and may have no equivalent of the vendor's conditions.

Each mismatch creates uncovered exposure. A customer claim that falls outside the vendor's covered plan, exceeds the vendor's cap, or arises from code generated while a required setting was off may leave you paying under your own indemnity with no upstream recovery. Notice timing matters as well. If your customer takes weeks to tell you about a claim and the vendor requires prompt notice, the delay can weaken your position.

NIST's draft Generative AI Profile suggests updating third-party contracts, service agreements and warranties to address generative AI risks, and notes that they may include GAI-specific indemnity clauses. The FTC has also described liability apportionment among users, tool developers and dataset developers as an open question, and has observed that large firms may have the resources to indemnify users. Neither point settles how your contracts should allocate risk, so assume nothing about default allocation and read the actual terms.

Why enforcement and provenance determine whether a claim is supportable

A vendor condition such as an enabled filter is true or false at a specific moment: when the code was generated. A settings screen checked during procurement, or an annual attestation, does not show what was in force for one function merged into a release eighteen months ago. Support for a claim therefore depends on records created at the point of generation and tied to the code that resulted.

Two kinds of record matter. The first is configuration and policy state: which safeguards were active, which policy applied, and what the system did with the interaction. The second is code provenance: where the output came from, what licence context applies to it, and what security context surrounds it. Together they let legal and engineering teams answer a claim by reference to a particular piece of code rather than by general assertion. NIST's draft suggestion to screen generative AI outputs against copyrights and other IP rights points in the same direction, and NIST's overlay concept treats configuration settings as a distinct AI system component worth capturing.

Trussed enforces policy in the execution path of coding assistants, with outcomes of allow, redact, block, rate limit or escalate for human approval at the level of individual interactions and tool calls. It also provides code provenance covering the origin, licence and security context of code. Because enforcement happens at runtime rather than being reviewed after the fact, the audit-ready evidence it generates records what was permitted when the code was produced. This supports a claim file but does not by itself establish coverage under any vendor's terms, which still depends on the contract.

Practical next steps

Start with an inventory. List each AI coding tool in use, the plan tier, and the vendor's indemnity conditions, caps, exclusions and notice duties. Set these beside the indemnity language in your standard customer agreements and mark every point where your commitment is broader than the protection behind it. Counsel can then decide whether to narrow customer terms, negotiate vendor terms, or accept the residual exposure knowingly.

Next, decide what record each condition needs and who holds it. Prefer records you retain under your own control, with retention and data residency you can configure, over records that depend on a vendor's retention choices. Finally, test the process with a mock claim: pick one released component and try to produce the settings state, origin, licence context and notice timeline within a short period. Where that exercise fails, the failure shows what to fix before a real claim arrives.

If you sell to government customers, check whether any acquisition clauses on audit trails or non-adherence notice apply to you. Confirm their current status as of November 2026 before relying on them.