AI-enabled features change the legal and commercial risk profile of SaaS and software products. We help product teams, legal teams and leadership groups assess whether an AI feature can be launched with the right safeguards, customer terms and internal allocation of responsibility.
The review focuses on how the AI feature works in practice: what data is used, what output is generated, who relies on the result, whether human review is required, how errors are handled, and how the feature should be described to customers.
The result is a practical launch-readiness assessment that supports product decisions, customer communication and compliance with GDPR, the AI Act and relevant sector-specific requirements.
AI features are often launched within an existing SaaS or software product where customer terms, product documentation and internal risk processes were not written for AI. The feature may look like a natural product development, while still changing liability, data protection, customer expectations and regulatory exposure.
For suppliers, the risks may arise at several levels. Customer data may be used in new ways. Output may be misunderstood as recommendations, decisions or professional advice. Automation may affect the customer’s own legal obligations. An AI feature may also be subject to requirements under the AI Act, GDPR or sector-specific rules, depending on its use case and actual functionality.
For buyers and enterprise customers, the question is often whether the AI feature can be used in their own organisation with sufficient control. This requires clarity on data flows, human review, audit trails, information security, supplier responsibility, user instructions and how the feature may be used in regulated environments.
We help SaaS providers, software companies and AI suppliers review AI features before launch, major release or enterprise sales. The review is tailored to the product’s risk profile. It may be lighter for a limited assistant function and more extensive for AI-supported recommendations, predictions, automated workflows or features used in regulated sectors.
We analyse both the legal risk and how it should be managed commercially. This means that we do not only identify which rules may be relevant, but also how the risks should be translated into customer terms, product descriptions, internal decisions, sales material, policies and technical or organisational safeguards.
An AI feature launch review should normally answer questions such as:
We start by understanding the use case and the product’s actual functionality. This includes the role of the AI model, which systems it is integrated with, what data it processes, what output is created and who uses the result.
We then review the legal and commercial risk position. This may include GDPR, the AI Act, information security, intellectual property, liability allocation, customer contracts, data processing, third-party suppliers and sector-specific requirements.
Based on the analysis, we prepare practical recommendations for launch. The focus is on what needs to be in place before release, what can be managed through terms or instructions, and which questions should be escalated to product leadership, legal or management.
We assess whether the AI feature can be launched with the current contract structure, documentation and internal controls. The result is a clear assessment of what should be adjusted before launch and which risks can be accepted, mitigated or escalated.
We help update customer terms, product descriptions, acceptable use terms, DPAs, security schedules and documentation so that they reflect how the AI feature actually works. This may include data use, output, liability limitations, user responsibility, human review and restrictions on use in specific environments.
We analyse rights and restrictions relating to input, training data, customer data, prompts, logs, embeddings and generated output. This is particularly important where the AI feature relies on customer data, third-party models or re-use of data to improve the service.
We help define when human review is required, how users should be informed and how responsibility should be allocated between supplier, customer and end user. This reduces the risk that AI output is used in a way the product was not intended to support.
Where needed, we prepare a short decision paper for product leadership, management or the board. It summarises the key risks, recommended safeguards, contract changes and any issues that should be addressed before release.
A legal review before launch makes it easier to move from uncertainty to a controlled product decision. It helps the team understand which risks are business-critical, which can be managed through practical safeguards and which should be explained more clearly to customers.
For SaaS and software suppliers, the review can reduce friction in enterprise sales, strengthen customer trust and give sales, product and legal teams a shared basis for discussion. For buyers and customers, it provides better insight into whether the AI feature can be used in their own organisation with sufficient control.
The aim is not to slow down innovation. The aim is to create a launch that is legally thought-through, commercially usable and possible to explain to customers, management and regulatory stakeholders.
This service is particularly relevant for:
The first step is normally a focused review of the AI feature, its data flows, users, output and planned launch model. We then assess which legal and commercial questions must be addressed before release and which actions should be prioritised to enable a controlled launch.
