← Sticker Wall MODEL · DETAIL

AI-Powered Perfumery On-Chain Rights Confirmation and Digital Scent Asset Platform for Scenic Spots

1) Charging project service fees for customized AI scent solutions by scene; 2) Earning royalties by licensing on-chain

MODEL

Key Fields

FIELD STAMPS

IndustryContent / Creator Economy

RegionChina

ScaleSME

ChannelHybrid

📌 Background

In 2026, AI large model capabilities extended into the olfactory field, and blockchain-based rights confirmation accelerated its penetration into digital content production. Qianjing Qianwei debuted its AI perfumer on-chain application at the China International Supply Chain Expo (CISCE), matching scent tags to visual scenes and placing scent content on the blockchain. The initiative aims to establish a closed loop for the generation, rights confirmation, and trading of digital scent assets to meet the demand for immersive experience upgrades in cultural and tourism spaces.

👤 Target Customers

Target customers include operators of offline spaces such as cultural and tourism scenic spots, commercial real estate, and museums, as well as fragrance brands seeking unique scent copyrights. Buyers are space operators or brand owners.

💰 Revenue Streams

1) Charging project service fees for customized AI scent solutions by scene; 2) Earning royalties by licensing on-chain digital scent assets to brands; 3) Revenue from scent playback hardware leasing or system subscriptions.

🧮 Cost Structure

Costs for AI model training and scent algorithm R&D, blockchain storage and smart contract development, and offline venue partnership and equipment maintenance.

🛡️ Moat

Core focus on AI-generated scent algorithms combined with blockchain-based proof of existence to establish traceable copyrights, leveraging first-mover advantage in vertical scenarios like scenic spots.

🔑 Keys to Success

Collaborate with platforms like CISCE to establish brand endorsement.
Secure one or two benchmark projects in scenic spots.
Develop low-cost, compact receiver hardware.

⚠️ Risks

Significant gap between technical demonstrations and large-scale commercialization.
Uncertainty regarding compliance policies for digital assets.
Inconsistent reputation due to poor standardization of the scent experience.

🏢 Cases

Qianjing Qianwei demonstrated the first AI perfumer on-chain at CISCE, effectively giving large models a 'nose'.

📊 SWOT Analysis

Strengths

The combination of AI and blockchain is differentiated and aligns with the trend of digital asset rights confirmation.
Easy to integrate with cultural and tourism storytelling, facilitating exposure at expos and city promotional events.

Weaknesses

Low penetration rate of scent playback equipment and limited user reach channels.
Low brand awareness and unverified commercial maturity of the technology.

Opportunities

Cultural and tourism spots are seeking immersive experience upgrades; the model can be replicated in hotels, cinemas, and commercial spaces.
Potential to integrate with digital collectibles or membership benefits to attract younger users.

Threats

Cross-industry entry by traditional fragrance groups or large AI companies.
Lack of objective evaluation standards for scent algorithms; on-chain rights confirmation may be perceived as a gimmick.

Sources