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A VP of Product choosing an AI audio platform is making a decision that affects program timelines, product roadmap flexibility, compliance posture, and long-term commercial strategy. The evaluation should cover ten questions across six areas — and the answers should be specific enough to be verifiable, not general enough to be unfalsifiable. The platforms that cannot answer these questions with specificity are the ones most likely to create problems mid-program.

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Why platform evaluation requires structured questions

Platform vendors universally describe their platforms as fast to integrate, easy to use, and designed for scale. These claims are unfalsifiable without specific evidence — and they are made by platforms whose capabilities vary enormously in practice. A structured evaluation process replaces claims with evidence. It forces vendors to answer specific questions that reveal the actual capability, architecture, and commercial model of the platform rather than the marketing description of it. The questions below are designed to surface the information that matters for a product decision, not a procurement exercise.

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Area 1 — Chip platform compatibility

Question 1: Which SoC platforms does your integration layer currently support? This is the first question because it determines whether the evaluation is worth continuing. If the platform does not support the chip platform the product is being built on, the integration path requires a custom build that eliminates most of the timeline and cost advantages of using a platform at all. Ask for a specific list of supported chip platforms. Ask whether support is full — meaning the complete interaction layer is available — or partial, meaning some capabilities require custom integration work. Ask whether the product team’s target chip is on the roadmap if it is not currently supported, and what the timeline and cost implications of that are. Question 2: What does integration on a supported chip platform actually involve? A supported chip platform should mean minimal foundational integration work. Ask the vendor to walk through what a typical integration looks like week by week from contract signing to first integrated build. If the answer is vague — “it depends on your specific requirements” — push for a reference program they can describe. Platforms with real integration experience can describe a typical program concretely.

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Area 2 — Post-shipment evolution capability

Question 3: How does your platform deliver new features and services to devices after they ship? Post-shipment evolution is a claim every AI platform makes. The question is whether the infrastructure to support it actually exists. Ask specifically: what is the update delivery mechanism? How are over-the-air updates tested and rolled back if something goes wrong? What is the latency between a feature being ready and it reaching devices in users’ hands? Question 4: Can you give an example of a feature or service added to a live product post-shipment on your platform? This turns a claim into evidence. A platform with real post-shipment evolution capability should be able to describe at least one concrete example — what was added, to which product, how it was delivered, and what the user experience was. A platform that cannot provide a specific example is describing a planned capability, not a proven one.

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Area 3 — Services ecosystem

Question 5: What services are currently live in your ecosystem, and how are new services added? The breadth and quality of the services ecosystem determines the post-shipment commercial potential of a product built on the platform. Ask for a specific list of currently available services — not a description of the categories they operate in. Ask how new services are added: is there a self-service integration path for third-party developers, or does every new service require a platform-level integration project? Question 6: What is the commercial model for service integrations — who earns what when a user activates a service? Service integrations have commercial implications for both the brand and the platform provider. Understand exactly how revenue is shared, what the platform takes, what the brand earns, and what the third-party service provider receives. Platforms with opaque commercial models on service revenue are platforms where the brand’s post-shipment revenue potential is not fully defined.

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Area 4 — Compliance and data architecture

Question 7: How does your platform handle data residency and consent across multiple jurisdictions? This question surfaces the platform’s compliance architecture. Ask specifically which jurisdictions the platform is currently compliant in, how data residency is managed for products sold in the EU, US, and APAC, and how the consent architecture works for users in different regions. Ask whether the platform has been audited against GDPR or equivalent frameworks and what the outcome was. Question 8: Who is the Data Controller for user data collected through your platform — the platform or the brand? This is a legal question with significant commercial and reputational implications. The answer determines who bears responsibility if a data incident occurs and who owns the user relationship from a regulatory perspective. Both models are defensible, but the brand needs to know which one applies before signing.

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Area 5 — Commercial model and lock-in risk

Question 9: What does the commercial model look like at scale — how does pricing change as device volume grows? Platform pricing that is attractive at low volume can become constraining at scale. Understand exactly how the commercial model works as device volumes increase, as the service catalogue expands, and as the platform’s intelligence capabilities are added. Ask whether there are revenue share components that affect post-shipment monetisation, and what the total cost of the platform relationship looks like at the brand’s five-year volume projection.

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Area 6 — Platform viability and roadmap

Question 10: What is your SoC distribution strategy, and how does it ensure the platform remains viable at scale? This is the long-term viability question. A platform that depends on brand adoption to grow has a different risk profile from one that grows through SoC-level distribution — because SoC distribution means the platform’s installed base grows with device shipments rather than requiring individual brand acquisition. Ask the vendor how their platform reaches devices, what their SoC relationships look like, and what the roadmap looks like for chip platform coverage over the next two years.

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How Bragi AI answers these questions

The Bragi platform is built around SoC-level distribution — embedding the interaction layer into chip platforms so devices ship Bragi-ready by default. This is the answer to Question 10, and it is the structural difference between Bragi and platforms that depend solely on brand-by-brand adoption to grow. Bragi AI enables brands to build AI-enabled audio products with fast, easy control and a continuously expanding services ecosystem. The ten questions above are designed to surface exactly this kind of structural clarity — and Bragi’s answers to them reflect the platform architecture described throughout this documentation. For the full picture of what the Bragi platform provides, see What is Bragi AI?. For the build vs buy context that typically precedes this evaluation, see Build vs buy: AI audio software for hardware brands.