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Strong Face Plan Secures "Strong Face" Copyright, Solving the Pain Points of AI Content Compliance and Homogenization (Angel Round)

小贾诩2026-07-07 14:03
Reconova plans to raise funds to build the world's first AI-native real-person portrait copyright bank to solve industry pain points

As AIGC technology is reshaping the production pipelines of the film, television, advertising, and gaming industries with overwhelming force, two formidable challenges confront content creators: on one hand, the "perfect faces" generated by AI are mired in severe aesthetic homogenization, lacking soul and memorable distinctiveness; on the other hand, unauthorized usage of portrait rights is facing enormous legal uncertainties. In response to this industry landscape, the StrongFace Project is seeking $8 million in financing, with the goal of building the world's first AI-native real-person portrait copyright bank.

The funds from this financing round will primarily be used for the exclusive signing and acquisition of the first batch of 1,000 "Strong Faces", the development of the core technology platform, and the construction of a global copyright compliance system. The core logic of this project lies in, amid the irreversible trend of AI-driven content production, proactively securing highly distinctive and iconic "Strong Face" resources, and converting them into legal, commercially usable, and traceable digital assets.

I. Directly Addressing Industry Pain Points: From "Infringement Risks" to "Aesthetic Fatigue"

Currently, the production of short dramas, performance-driven advertisements, and NPCs in AAA games is fully embracing AIGC. Industry consensus indicates that 80% of film and television video content in the future may no longer rely on real-person live shooting. However, this improvement in efficiency comes at the cost of a diminished "sense of realism". Faces generated by mainstream models such as Midjourney and Stable Diffusion often conform to a template aesthetic of smooth skin and symmetrical features, leading audiences to experience severe "AI face aesthetic fatigue".

At the same time, copyright risks hang like the Sword of Damocles. One of the core triggers of the Hollywood strikes was actors' concerns over the usage rights and revenue distribution of their facial data after AI scanning. Currently, there is no platform in the market that can provide a real-person portrait library with "cleared copyrights, commercial usability, and confirmed ownership". The StrongFace Project has keenly identified this market gap: rather than letting AI generate generic, identical fake faces, it is better to turn the real "Strong Faces" in the real world — faces that hold stories in their wrinkles and carry unique tension in their asymmetries — into standardized fuel for AI content production.

II. Technical Closed Loop: Monetizing Assets from "Human Faces" to "Face DNA"

The StrongFace Project has built a complete three-tier system, aiming to solve the full-link problems ranging from asset acquisition to large-scale AI usage, and finally to revenue distribution.

On the asset side, the project team, following Hollywood agency logic, selects individuals around the world with striking skeletal structures, tribal markings, or rare facial features. The signing model adopts a combination of "high down payment + lifelong usage revenue sharing", and signs the "AI Portrait Full-Field Authorization Agreement" covering all scenarios such as film, television, games, and derivatives, thereby acquiring the exclusive or sole agency rights for the AI training and commercial use of their portraits.

On the technical ownership confirmation side, the StrongFace Project performs 3D light field scanning and multi-expression data collection for every face added to the library. The technical team not only generates standardized asset packages suitable for various AI models (including Embedding for training and LoRA weights), but also generates a unique "Face DNA" hash value through blockchain technology. This technical design means that any derivative content generated based on that face can theoretically be traced on the chain, providing compliance guarantees for clients.

On the transaction and revenue sharing side, the platform establishes a B2B2C business model. Clients such as AI video companies and game developers can access the StrongFace library through subscriptions or one-time purchases. The platform innovatively integrates smart contracts, which can automatically record every call, synthesis, and rendering action, and distribute revenue in real time at a ratio of 70% (face owner) to 30% (platform). This mechanism not only protects the long-term rights and interests of creators (face owners), but also forms a sustainable economic model of "earning a living with one's unique face".

III. Market Space and Future Outlook

The commercial blueprint of the StrongFace Project targets a new track with an annual scale exceeding tens of billions of dollars. As the AI video generation market is expected to surpass $32 billion by 2028, and the global gaming market's demand for "story-rich NPCs" continues to grow, the licensing value of a single human face has been verified to reach tens of thousands or even hundreds of thousands of dollars.

According to the plan, the StrongFace Project will complete the signing of 1,000 Strong Faces in the first phase (0-12 months), and reach seed cooperation with leading AI short drama companies and game developers; within the following two years, the platform will gradually expand its library to more than 30,000 faces, forming the world's largest real-person AI portrait copyright pool, and attempt to launch the Strong Face rating standard to grasp the industry's pricing power.

For the content industry, when AI makes "content creation" completely accessible to everyone without barriers, what is truly scarce is precisely those human, irreplicable faces. The emergence of the StrongFace Project not only aims to solve the current compliance and aesthetic pain points, but also attempts to establish a new order regarding digital identity and portrait value before the boundary between the virtual and the real is completely blurred.