01
Evidence collection
Documents, financial statements, certificates, results and verifiable data are collected as the initial basis of the process.
Value Engine
Transform documented evidence into structured real value.
The PLUS Value Engine helps companies and individuals identify, organize and validate the value generated through verifiable data, results and documents. Its purpose is to make this value legible, demonstrable and progressively activatable.
Demonstrable value
The problem is not creating value. It is proving it.
Many companies and individuals generate value every day. Yet this value often remains scattered across documents, financial statements, learning paths and experiences that are difficult to interpret consistently. PLUS is designed to transform this evidence into a structured, verifiable and usable representation.
PLUS method
From documented value to structured representation.
The Value Engine follows an ordered pipeline that transforms verifiable evidence into organized, validated and usable information for reports, scoring and token preview.
02
Analysis and organization
Information is read, organized and made easier to interpret in order to build a first structured view.
03
Validation and normalization
The system checks coherence, quality and completeness, reducing informational noise and ambiguity.
04
Value assessment
Evidence is translated into a prudential reading of value, based on traceable and defensible criteria.
05
Report production
The result is synthesized into a readable output for analysis, comparison, decision support and further validation.
06
Token preview
The system shows a preliminary and non-binding representation of a possible future tokenized layer.
Value areas
Two forms of value, one recognition method.
The PLUS Value Engine applies a common logic to companies and individuals: start from verifiable evidence, organize it, validate it and transform it into a structured representation of value.
Company value
From financial statements to demonstrable economic value.
The system analyzes economic and operational evidence to build a structured representation of the company's value.
Analyzes
- Financial statements
- KPIs and performance
- Contracts
- Certifications
- Documentable assets
- Company history
Output
- Structured evidence
- Documented valuations
- Verifiable reports
- Token preview based on company value
Human capital
Making visible the value generated through study, training and experience.
The system analyzes documentable evidence linked to a person's educational and professional path to build a structured representation of the value generated over time.
Analyzes
- Academic degrees
- Certifications
- Specialized training
- Professional experiences
- Documentable activities
- Expenses sustained for personal growth
Output
- Structured evidence
- Verifiable report
- Weighted valuation
- Token preview based on uploaded evidence and PLUS weightings
Digital representation
From value measurement to digital representation.
The Value Engine represents the first layer of the PLUS REALISTIC MODEL infrastructure. The generated reports provide the basis for future processes of attestation, digital representation, tokenization and the development of new models for recognizing economic value and human capital. This evolution is particularly relevant in contexts of innovation, education, sustainability and skills development, where the ability to measure and enhance evidence plays an increasingly central role.