Destiny Analysis Engine: Symbolic Reasoning + Vector Relation Analysis
The Destiny Analysis Engine is the self-developed capability base: it integrates professional knowledge, analysis rules, and algorithms to compute multi-dimensional analyses from personal information, producing identifiable, storable, callable, continuously updatable individual data. The engine itself is not sold — it is the shared base of all three products.
Two Core Methods
Symbolic Reasoning: reverse-engineering expertise
Converts implicit judgment processes from texts, formulas, schools, and experience into explicit, executable rule systems. Output is deterministic, traceable, explainable, reproducible, and maintainable.
Vector Relation Analysis: original modeling
Organizes destiny entities, attributes, relations, and states into an analyzable vector space, computing states, trends, sensitive variables, and transformation conditions under multi-variable interaction.
How the Two Methods Work Together
| Aspect | Symbolic Reasoning | Vector Relation Analysis |
|---|---|---|
| Nature | Reverse-engineers existing judgment systems | Original modeling of destiny entities and relations |
| Core question | Which rule fired and why this result | Which variables are acting and what state they form |
| Strength | Stable, clear-path, reproducible | Multi-dimensional, dynamic, relational, extensible |
| Output | Rule judgments with evidence | Relation structures, mechanisms, states, trends |
Symbolic Reasoning supplies rule basis, baseline judgments, and evidence anchors; Vector Relation Analysis places base states into life stages, environments, and relation networks. The former answers "why is it so", the latter "where is it heading".
What the Engine Does
- Computes relatively stable base structure and personal traits
- Analyzes talent, physiology, emotion, psychology, thinking, personality, behavior
- Analyzes career, wealth, marriage, family, health domains
- Computes relations with family, partners, clients, and other subjects
- Computes state changes across life stages and time cycles
- Identifies favorable/unfavorable factors, causality, and risk conditions
- Produces standardized results and individual data feeding all three products
AI's Role
AI handles understanding, interaction, and expression — it never replaces professional computation: natural-language interaction and content translation in three style levels (public / enthusiast / professional). Rule-layer computation does not depend on LLMs; on model failure the system explicitly falls back to deterministic results.