Problem
VicTy solves the challenge of having a belief or thesis about the future and transforming it into an informed investment decision. People often have convictions about economic trends (such as the impact of artificial intelligence on the energy sector), but they run into the complexity of knowing suitable assets, mapping risks, and navigating financial and crypto asset markets. The platform fills this gap by translating ideas into real economic exposures and into comprehensible portfolios, explained and adjustable by the user.
Solution
Based on the VicTy repository, VicTy proposes to solve the problem through an experience structured in pillars and steps:
- Thesis Engine: Uses artificial intelligence integration to translate user beliefs and subjective ideas into comprehensible investment portfolios, providing the rationale behind each choice and explaining the limitations of each asset.
- Curated Catalogue: Works with a restricted and validated selection of financial instruments, ensuring that the user understands the relationship between the thesis, the asset and its risks before making any decision.
Educational Approach (Understand before investing): The process guides the user from the expression of a belief to the review of economic exposures, portfolio simulations, and secure approvals via compatible portfolios (such as Solana), prioritizing transparency and control.
Business model
The VicTy business model is structured around three potential revenue sources currently under validation:
- Execution: Collection of a transparent fee on the financial volume actually executed through the platform's integrations and swap routes.
- Strategies (SocialFi): Revenue sharing with creators and experts whose strategies and theses drive active executions by the community.
- API-first: Usage, licensing, or revenue sharing fees for the distribution and integration of thesis intelligence into portfolios, apps, and partner agents.
Average ticket: As the platform operates focusing on the translation of theses for tokenized and decentralized portfolios (with future execution via protocols such as Jupiter), the expected average ticket varies according to user activity, consisting of percentage or fixed fees proportional to the volume traded in the simulated and effective allocations.
Market
VicTy's global target market encompasses the intersection between global wealth management platforms, self-service tools for retail investors, and the decentralized cryptocurrency and finance ecosystem (DeFi/Web3). While there are no closed consolidations of exact static size for the specific intersection of artificial intelligence thesis translation into decentralized portfolios, the total addressable market (TAM) encompasses the hundreds of millions of global retail investors and crypto asset users seeking intuitive education and allocation tools. The target service market (SAM) focuses on active users of Web3 platforms and non-custodial custody applications that demand portfolio automation, asset curation, and transparent conviction-based execution.
Competitors
Basket. co
Competitive differentiation
Both of the mentioned projects have already won the Solana hackathon, however, both do not have fully developed functionalities, and none of them actively uses AI for active suggestions, but they work with pre-defined models and without the flexibility to actively customize the investment basket user.
Entry barrier
VicTy's competitive advantage lies in the unique combination between the Thesis Engine (an artificial intelligence engine specialized in translating subjective convictions into comprehensible investment portfolios, with rationale and analysis of limitations) and an architecture focused on transparency and education (Understand before investing).
The entry barrier is supported by three pillars:
Curated Catalog and Risk Validation: Strict curation and server-side validation that connects theses to real economic exposures without filling the portfolio with disjointed assets.
SocialFi Layer and Creator Economy: An ecosystem for discovering, adapting, and sharing strategies created by experts and communities.
API-first strategy: Modular architecture designed to bring thesis translation intelligence directly to portfolios, applications, fintechs, and agents, generating a unique network effect.