wavebird
Quick answer
wavebird is ad infrastructure for consumer AI apps, founded by Mario von Bassen and operated by MC Squared UG in Munich, Germany. It connects applications to global ad demand through one integration, with labeled placements kept separate from model instructions and generated output.
What wavebird is
wavebird serves teams building consumer AI products: chat and assistants, music and audio tools, image, video and 3D generation, app builders and other AI experiences. Product, growth, founders and finance can evaluate the economics and controls; developers use the API and SDK to connect the app.
The API and SDK give the publisher control over when an ad is requested, where it can render, which formats are allowed, and how no-fill behavior should work.
How it works
wavebird runs ad selection in parallel with model generation, so the model response path does not wait for an ad decision.
The app keeps the AI answer primary, and any sponsored placement renders in a separate slot the publisher controls.
Privacy and proof
The default delivery path is data-minimizing: prompts and chat history are not sent to SSPs, DSPs, advertisers, or other ad partners.
wavebird reduces allowed context into delivery metadata, applies consent and blocking rules, and records tamper-evident proof for billable impressions.
European roots. Global ad demand.
Built in Europe, wavebird gives consumer AI apps access to the global advertising market through established advertising partners. Publishers do not need to build their own advertiser sales operation. Demand, eligibility rules and geography affect which ads are available.
wavebird acts between publishers and advertisers. Publishers need control over their product and revenue; advertisers need suitable environments and transparent measurement. The infrastructure supports that exchange through placement controls, data minimization and traceable delivery records.
Helping shape advertising in AI
As a pioneer in advertising for consumer AI, wavebird develops both practical infrastructure and principles for how ads can fund AI without influencing its output. Its mechanism for ads during generation is patent pending; a patent has not been granted.
Founder Mario von Bassen co-authored the February 2026 Compute Sponsoring paper with Christian Leinberger. The current September 2026 publication, by Christian Leinberger, proposes a category definition linking an ad exposure to an identifiable compute unit. It sets out separation, data sovereignty and consent principles. It is a published proposal, not a formally adopted industry standard. Read the current paper or the February 2026 version.
The implementation is documented in the API and SDK guides. The engineering evidence, proof-integrity explanation and data protection review describe the tests, records and safeguards behind it.
What wavebird does not do
wavebird is not an SSP, DSP, ad network, website ad server, analytics platform, or a system that rewrites model prompts or model output.
- It does not send prompts or chat history to ad partners.
- It does not make sponsor information part of the model request or response.
- It lets the publisher choose suitable placements and timing within consent, safety and partner requirements.
Main paths
See how it works and the ad revenue guide to evaluate your product's business case. Share the API docs with your engineering team when planning the integration.
Use Contact for product, commercial, privacy or technical questions.
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