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Do not treat an AWS AI competency badge as a guarantee. It is a useful screening signal, backed by AWS technical validation and customer-success evidence, but it does not set a partner’s price, scope, service levels, liability, intellectual-property ownership, data practices, or exit obligations. Before signing, verify the legal counterparty and delivery team, turn the use case into testable deliverables, model every AWS and vendor charge, and negotiate explicit rules for data, prompts, outputs, code, security, support, remedies, and portability.
What an AWS AI partner actually does
The AWS Partner Network (APN) is a global community that helps partners build, market, and sell customer solutions. AI work can come from several partner types, not just one kind of consultancy:
- Consulting and service partners that assess, design, build, migrate, integrate, operate, or support systems.
- Software partners that provide applications, platforms, monitoring, security, or workflow products running on or alongside AWS.
- Foundation-model providers and specialists that offer model access, customization, evaluation, or fine-tuning.
- Data and infrastructure specialists that handle pipelines, storage, retrieval, networking, accelerators, and observability.
- Security and responsible-AI providers that address identity, privacy, governance, testing, risk management, and policy controls.
AWS says Generative AI Competency Partners can support adoption and strategy, application build and testing, model training or customization, operations, security, responsible-AI frameworks, and infrastructure or data work. Competency status means AWS has validated specified technical capabilities and reviewed customer-success evidence. It does not mean AWS is guaranteeing your project’s result, endorsing a particular statement of work, or becoming responsible for the partner’s performance.
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1. Verify the counterparty, authority, and delivery team
Start with the entity that will actually be liable if the project fails. Marketing names, AWS Partner profiles, and Marketplace listings may not identify the same legal company.
Checks to complete before commercial negotiations
- Record the exact legal name, registration details, address, tax identity, and contracting entity.
- Check the partner’s AWS profile, claimed competency or specialization, certified personnel, service regions, and the date those claims were verified.
- Identify the people who will design, build, secure, and operate the system. Ask which work is done by employees and which by subcontractors.
- Request references for the same workload, industry, data sensitivity, model type, and operating scale. Ask the reference how handover, incidents, overruns, and termination were handled.
- Confirm professional-liability, cyber, errors-and-omissions, and other insurance limits, and ask whether coverage applies to subcontracted work.
- Confirm governing law, venue, tax treatment, renewal owner, and who has authority to approve scope or price changes.
Know which commercial path you are signing
| Arrangement | What to confirm |
|---|---|
| AWS Marketplace listing | Whether the purchase is software, professional services, or both; which terms are incorporated; and which AWS services or infrastructure are billed separately. |
| Private offer | Negotiated price, term, payment schedule, renewal behavior, and any amended end-user license terms. Confirm what happens when the offer expires. |
| Direct statement of work | The legal entity, detailed deliverables, acceptance process, change control, payment milestones, and liability terms signed directly with the provider. |
| Bundled arrangement | Which party supplies each component, who supports it, and whether a failure by one supplier excuses another supplier’s obligations. |
AWS states that Marketplace buyer-seller agreements are between the parties and that AWS is not a party to those agreements. Do not assume an AWS checkout flow gives you a claim against AWS for a partner’s missed milestone, data incident, or unpaid refund.
2. Turn the AI idea into measurable scope
“Build a generative-AI solution” is not an acceptance criterion. Put the intended business outcome and the technical boundaries in the statement of work.
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Define the system and the work
- State the business outcomes, users, jurisdictions, in-scope workloads, environments, integrations, and operating hours.
- Name the proposed models, AWS services, data stores, retrieval components, guardrails, evaluation tools, and deployment environments—or require a documented approval process for substitutions.
- List milestones such as discovery, architecture, prototype, security review, pilot, production launch, and operations handover.
- Specify deliverables: source code, infrastructure-as-code, prompts, configuration, evaluation sets, runbooks, diagrams, threat models, model cards, training, and administrator documentation.
- State customer dependencies, including data quality, access credentials, subject-matter experts, approvals, and response times. A missed dependency should trigger a defined schedule adjustment, not an unlimited change to price.
- Write explicit exclusions, such as data labeling, legacy-system remediation, 24-hour operations, regulated advice, or model retraining.
Make acceptance testable
For each deliverable, define the test, test data, evaluator, deadline, and pass threshold. Depending on the use case, that could include response latency, availability, retrieval precision, grounded-answer rate, refusal behavior, toxicity or privacy tests, cost per transaction, throughput, or human-review accuracy. If a quality metric cannot be measured reliably, specify a review process and a re-performance obligation rather than promising an undefined “accurate” system.
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Use a written change-request process: who may request a change, how the provider estimates effort and AWS consumption, the approval deadline, and whether work can begin before a signed change order. Marketplace professional-services guidance calls for clear categories such as assessment, implementation, managed services, premium support, or training, together with a clear value proposition, support description, and straightforward service terms. Make your statement of work at least that specific.
3. Model the full price, including AWS usage
The quoted partner fee is rarely the total cost of an AI deployment. Separate one-time, recurring, usage-based, and pass-through charges before comparing bids.
| Cost component | Contract question |
|---|---|
| Fixed professional fees | What deliverables and acceptance events are included, and what triggers the next payment? |
| Time and materials | What roles, hourly or daily rates, minimum increments, travel rules, and not-to-exceed cap apply? |
| Model and API consumption | Who pays for input and output tokens, embeddings, fine-tuning, evaluations, and retries? Which model-price assumptions are used? |
| AWS infrastructure | Who pays for compute, storage, databases, networking, data transfer, accelerators, backups, and environments outside the Marketplace transaction? |
| Operations and observability | Are logging, tracing, monitoring, alerting, incident response, and on-call coverage included or metered separately? |
| Support, taxes, travel, and third-party licenses | Are support tiers, tax, travel, open-source obligations, and non-AWS licenses itemized? |
| Renewal and committed spend | Are there automatic renewals, rate increases, minimum commitments, or discounts that disappear if usage falls? |
AWS specifically warns in its Marketplace professional-services guidance that customers may owe additional AWS infrastructure charges outside the Marketplace transaction. Put account ownership and billing visibility in writing. Require budgets, anomaly alerts, approval thresholds, daily or weekly usage reports, and a rule assigning responsibility for overages caused by provider design, misconfiguration, or unauthorized experimentation.
For private offers, record the negotiated duration, payment schedule, pricing model, and amended license terms. Ask what happens to prepaid amounts, discounts, and reserved capacity if the project is paused, cancelled, or terminated for cause.
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4. Protect data and govern AI behavior
AI contracts must cover more than ordinary application hosting because prompts, retrieved documents, outputs, evaluation data, telemetry, and fine-tuned artifacts can each contain sensitive information.
Data and security provisions
- Define controller, processor, and independent-controller roles for each data flow.
- List permitted inputs and prohibited data, retention periods, deletion deadlines, backup handling, and deletion certificates.
- Specify AWS Regions, processing locations, cross-border transfers, subprocessors, and the process for approving a new subprocessor.
- Require encryption in transit and at rest, key ownership or customer-managed keys where needed, least-privilege access, credential rotation, and access logging.
- Set incident-notification deadlines, investigation cooperation, evidence preservation, regulatory assistance, and costs of required notices.
- Require security assessments, vulnerability remediation targets, audit reports, penetration-test summaries, and a right to obtain reasonable audit evidence.
Prompt, output, and model-training rules
State whether the partner may store prompts and outputs, for how long, and for which operational purposes. Prohibit using customer data, prompts, outputs, fine-tuning sets, or telemetry to train a shared or third-party model unless you give explicit written approval for that precise use. Define who may access human review queues and how reviewers are bound to confidentiality.
Address model and provider changes: notice before changing a model, testing of a replacement, rollback rights, and treatment of a model that is withdrawn or materially altered. Require records of model versions, system prompts, retrieval indexes, safety settings, and evaluation results so another team can reproduce the production behavior.
AWS Marketplace’s Standard Contract can be paired with an Enhanced Security Addendum or a HIPAA Business Associate Addendum. Those standardized options do not eliminate the need for product-specific commitments covering configuration, support, data flows, retention, and service levels.
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5. Set performance, support, and remedies
AI quality varies by workload, data, and model version, so combine conventional service levels with measurable quality and operational duties.
| Area | Terms to specify |
|---|---|
| Availability | Monthly uptime percentage, measurement method, exclusions, maintenance windows, and dependency treatment. |
| Incident response | Severity definitions, acknowledgement and restoration targets, escalation contacts, and 24-hour coverage if required. |
| Model quality | Use-case-specific thresholds for groundedness, retrieval, refusal, latency, throughput, or human-review accuracy, plus test frequency. |
| Monitoring and reporting | Dashboards, cost reports, drift alerts, security events, evaluation reports, and access to logs. |
| Remedies | Service credits, re-performance at no charge, corrective-action plans, fee refunds, and termination rights for repeated or material failures. |
AWS requires Marketplace professional-services listings to identify support contacts and the level of support customers can expect. Its guidance says customers should be contacted within two business days after a listing inquiry or private-offer acceptance unless the offer states otherwise. Treat that as a Marketplace communication expectation, not as an uptime or incident-resolution SLA for your production system.
Specify maintenance notice, emergency-change authority, root-cause analysis deadlines, and how unresolved defects affect acceptance or payment. AWS notes that standardized terms do not replace product-specific configuration, support, and SLA terms; your contract must supply those details.
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“The customer owns the AI” is too vague. Separate each asset and state the license or ownership outcome.
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| Asset | Term to negotiate |
|---|---|
| Customer data and documents | Customer ownership, limited processing license, confidentiality, return, deletion, and no unrelated training. |
| Customer-owned code and configurations | Ownership or perpetual, transferable license; delivery of source, infrastructure-as-code, and build instructions. |
| Prompts, evaluations, and outputs | Who may use them, whether they may be reused or disclosed, and how they are exported at exit. |
| Fine-tuning data and artifacts | Ownership, model-provider restrictions, retraining rights, and whether the artifact can run without the partner. |
| Partner pre-existing materials | A clear license, scope, term, geography, user limit, and treatment if the relationship ends. |
| Open-source and third-party components | Bill of materials, license obligations, source-offer requirements, and approval for restrictive licenses. |
| Models and model licenses | Permitted use, geographic limits, attribution, output rights, usage restrictions, and change or retirement procedures. |
Add confidentiality, security obligations, infringement and data-breach indemnities, insurance requirements, warranty disclaimers, liability caps and carve-outs, governing law, venue, dispute process, and audit rights. AWS says its standardized Marketplace terms address use rights, warranty, indemnification, governing law, and data/privacy concerns, while AWS Partner Network terms require partners to act professionally and competently, comply with law, and avoid harmful, false, or deceptive practices. Those framework obligations do not replace negotiated protection for your particular system.
7. Plan termination and portability before launch
Exit terms are easiest to negotiate before the partner has control of the code, accounts, prompts, and production knowledge.
- Include termination for convenience, termination for cause, cure periods, insolvency rights, and immediate suspension rights for security or legal risk.
- Define a transition period, hourly rates or included hours, knowledge-transfer sessions, runbooks, architecture diagrams, and replacement-vendor cooperation.
- Require export in usable formats for source code, infrastructure definitions, prompts, evaluation sets, model configurations, indexes, logs, and billing records.
- Specify credential handover, account ownership, access revocation, key rotation, and deletion of partner-held copies, including backups, with a written deletion certificate.
- State whether prepaid fees are refundable, which committed AWS charges remain payable, and whether termination fees apply.
- Address Marketplace renewal, EULA updates, amendments, and private-offer expiry. AWS documents that these mechanics depend on the offer type and pricing model.
Require the partner to keep your AWS account, repositories, domains, model endpoints, and encryption keys under your control wherever practical. A provider-managed account can make a technically successful project commercially difficult to leave.
8. Compare providers with an evidence-based matrix
Use AWS Partner Solution Finder to filter by category, use case, workload, specialization, certification, and Region. AWS reports a partner network spanning 198 countries, so a broad directory result is not proof that a provider can serve your jurisdiction or support your operating hours.
| Criterion | Evidence to request |
|---|---|
| AWS validation and relevant experience | Applicable competency or specialization, named certified staff, architecture examples, and references for comparable work. |
| Architecture and model expertise | Design review, model-selection rationale, evaluation plan, fallback strategy, and documented assumptions. |
| Security and responsible AI | Data-flow diagram, control mapping, incident process, testing approach, and subprocessor list. |
| Delivery discipline | Milestones, acceptance tests, staffing plan, dependencies, change-control form, and escalation path. |
| Total cost | Rate card, AWS usage model, token assumptions, overage controls, renewal terms, and support charges. |
| SLA and remedies | Availability and response targets, quality measures, reporting, credits, re-performance, and termination triggers. |
| IP and data terms | Ownership matrix, training restrictions, licenses, indemnities, liability cap, and audit rights. |
| Exit and portability | Export formats, account ownership, transition assistance, deletion proof, and replacement-vendor cooperation. |
Weight the matrix for your risk rather than awarding points for badges alone. A local legal entity, language coverage, data-residency capability, and support coverage may matter more than a broader geographic footprint. Ask each finalist to price the same scope and disclose subcontractors so that the comparison is between equivalent obligations.
9. Red flags that should stop signature
- The seller will not identify the legal entity, delivery personnel, subcontractors, or insurance carrier.
- The proposal promises “accurate” or “hallucination-free” output without a test set, threshold, evaluator, or remedy.
- A low project fee omits AWS infrastructure, model tokens, data transfer, observability, support, or taxes.
- The partner claims the competency badge means AWS guarantees the work, or refuses to state that AWS is not the contracting party.
- The contract grants unrestricted rights to prompts, outputs, telemetry, or fine-tuning data, including training shared models.
- All code, credentials, model settings, and logs sit in a provider-controlled account with no export or transition obligation.
- There is no cure period, re-performance duty, service credit, or termination right for repeated SLA or security failures.
10. A practical signing sequence
- Write the use case, regulated data categories, target users, Regions, and success metrics internally.
- Shortlist partners through AWS Partner Solution Finder and verify legal entity, references, staffing, and subcontractors.
- Issue identical scope and pricing assumptions to finalists; require separate lines for partner fees and AWS or third-party consumption.
- Review architecture, data flows, model-training behavior, security controls, and portability before selecting a preferred bidder.
- Negotiate the master agreement, statement of work, SLA, data-processing terms, IP schedule, private offer or Marketplace terms, and exit plan as one package.
- Run acceptance tests in a controlled environment, confirm billing alerts and logging, and obtain the documentation and access needed for operations before production launch.
The decision is ready when you can answer, in writing, who is liable, what will be delivered, how success is measured, what the maximum cost is, who controls every data and code asset, what happens during an incident, and how you will leave without losing operational capability.
Quick Recap
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