Zyno AI Engine
Multi-Agent
System
The 24-agent orchestration system that transforms user intent into on-chain artifacts.
System Overview
Zyno coordinates 24 specialized agents to transform natural language intents into production-ready code and transactions.
LLM Base
GPT-5.1-class models with Structured Outputs and JSON Schema validation.
Knowledge Base
RAG (Retrieval-Augmented Generation) engine utilizing a vector database of Solana docs.
Orchestration
AEPO & AECO engines for managing individual pathways and group cohorts.
Output Format
Standardized, schema-validated UI Blocks for consistent frontend generation.
Agent Capabilities
24 Specialized Agents working in concert.
Architect
System design, technical architecture, and Solana program structure.
Engineer
Smart contract generation, Anchor scaffolding, and code auditing.
CFO
Tokenomics modeling, financial projections, and treasury management.
Guide
User orientation and pathway alignment.
Onboarding
Platform setup and initial configuration.
Education
Learning content creation and curriculum personalization.
Builder
Project implementation and milestone tracking.
Token
SPL token management, minting, authorities.
NFT
Collection generation, metadata, Metaplex integration.
DAO
Governance design, proposal templates, voting logic.
Security
Threat modeling, vulnerability assessment, hardening.
Audit
Automated code review, pattern analysis, safety checks.
Execution Flow
How Zyno processes your requests.
User Natural Language Input
User describes their project, question, or request in plain language.
Zyno Core (Intent Analysis)
Analyzes user intent, classification, and context.
Agent Selection & Routing
Routes to relevant agents (e.g. Architect, Engineer, CFO).
Parallel Execution & RAG
Agents work simultaneously, querying the Knowledge Base for Solana-specific data.
Output Synthesis & UI Generation
Merges outputs and creates structured UI elements for the user.
API Integration
Directly access the orchestration layer.
/api/zyno/orchestrate
Main entry point for interacting with the agent swarm.
"Authorization": "Bearer <SIWS_JWT>"
}
Payload
"intent": "Create a DAO for my renewable energy project",
"context": {
"project_id": "proj_123"
}
}