Technical Overview

Overview

KOLI integrates Web3 technology with a self-developed multimodal AI architecture to construct a decentralized and trustworthy AI model stack. This stack is built upon three core logical layers: the AI Engine Layer, the Web3 Protocol Layer, and the Multimodal Generation Layer. By organically combining large-scale model capabilities with blockchain protocols, it establishes a unified framework for multi-device coordination, trustworthy intelligent agent interaction, and multimodal content generation. This technical section of the whitepaper will provide a detailed explanation of the core architectural design principles and modular components of the KOLI model stack, and describe how each submodule works together to form a complete system.

  • AI Engine Layer

  • Web3 Protocol Layer

  • Multimodal Generation Layer

Model Stack Architecture Overview

KOLI’s model stack follows a layered architectural pattern, divided into three distinct tiers:

  • The AI Engine Layer at the foundation

  • The Web3 Protocol Layer at the center

  • The Multimodal Generation Layer at the top

Each layer serves a specific functional purpose and is connected via well-defined interfaces, forming a clear and tightly integrated system. The following is a structured breakdown of the layers and their primary components:

KOLI Model Stack Architecture:
├─ AI Engine Layer
│   ├─ EnginePool (Codename: ADH)
│   │   ├─ ASR Engine (Automatic Speech Recognition)
│   │   ├─ LLM Engine (Large Language Model)
│   │   └─ TTS Engine (Text-to-Speech)
│   └─ ... (Other AI capability engines, extendable)
├─ Web3 Protocol Layer
│   ├─ x402 Payment Protocol Integration
│   ├─ ERC-8004 Trust Agent Standard
│   ├─ Blockchain Smart Contract Deployment
│   └─ AgentPool Module (Multi-device AI Agent Pool)
└─ Multimodal Generation Layer
    ├─ LLM (Large Language Model – text generation)
    ├─ LASM (Large Audio-Speech Model – audio comprehension and synthesis)
    ├─ LVLM (Large Vision-Language Model – image/visual processing)
    └─ LVM-Video (Large Video Model – video content generation)

As shown above:

  • The AI Engine Layer delivers foundational model computing power.

  • The Web3 Protocol Layer ensures decentralized interaction and value transmission.

  • The Multimodal Generation Layer enables intelligent content creation as experienced by end users.

These layers are interconnected through standardized APIs:

  • The engine layer provides a unified AI model invocation interface for use by the generation layer.

  • The protocol layer underpins both the engine and generation layers with on-chain identity, payment settlement, and trusted execution capabilities.

The sections that follow will explore each layer’s detailed design and modular implementation.

Technical Architecture & Model System

Dual-Core System Design: AI-Native + Web3-Native

From day one, KOLI has adopted a dual-core technical architecture—AI-native compute combined with Web3-native infrastructure—to deliver globally adaptive intelligent experiences anchored in trustless blockchain systems.

The architecture is structured across three major layers:

KOLI System Architecture
├── Frontend Layer (User Interface & Access)
├── AI Engine Layer (LLM + LASM + LVLM)
└── Web3 Backend Layer (Smart Contracts, Oracle, Wallet Identity)

Frontend Interfaces

  • Web App & Mobile App: Core interface for interacting with KOLI’s digital companions and DeFAI tools.

  • Browser Extension: Enables on-site interaction with KOLI avatars directly on X (Twitter) and other social platforms.

  • Future VR/AR Support: Immersive interfaces to engage with AI twins in 3D virtual environments (Oculus, Apple Vision Pro).

AI Engine Layer: LLM + LASM + LVLM Stack

The AI engine layer powers KOLI's digital KOL clones and intelligent agents with multimodal capabilities:

  • LLM (Language Model): Built on advanced transformer architecture and fine-tuned on crypto-native corpora.

    • Training data includes: historical KOL tweets, industry news, token whitepapers, exchange reports.

    • Result: Context-aware responses with realistic tone and KOL-style reasoning.

  • LASM (Large Audio-Speech Model):

    • Voice cloning using few-shot training from 2–5 mins of KOL audio.

    • High-fidelity TTS and speech-to-text integration.

  • LVLM (Vision-Language Model):

    • Facial expression-driven avatar rendering.

    • Lip-sync animation powered by GAN-based modeling.

  • Emotional and Personality Conditioning:

    • Each digital twin maintains consistent personality traits—humorous, rational, etc.—for coherent, authentic interactions.

{
  "persona_id": "0xKOLI789",
  "style_embedding": "bullish-sarcastic",
  "voice_clone": "sampled_from_Twitter_Space.wav",
  "avatar_motion_model": "GAN-LVLM-v2"
}

Web3 Backend Layer

The blockchain layer supports decentralized identity, financial execution, and trust assurance.

  • Wallet Binding: Each user and digital KOL is linked to a Web3 wallet.

  • BNB Chain Contracts:

    • $KOLI token issuance and transfer logic

    • Yap point redemption

    • DeFAI transaction handlers

    • x402/x8004 protocol bridges

  • Oracle Integration: Ensures real-time sync of payment receipts, data feeds, and agent task triggers.

All sensitive events (e.g., payments, asset transfers) are executed on-chain for transparency and auditability.

Model Training Pipeline

KOLI models are built using a hybrid of open-source foundation models and proprietary fine-tuning on crypto-specific corpora.

Modality
Training Source
Specialization Purpose

LLM

Open-source transformers + crypto tweets, docs

Domain-specific reasoning, KOL tone emulation

Voice/TTS

Few-shot KOL speech samples

Realistic voice cloning for interactive avatars

Vision (GAN)

Avatar templates + real KOL image references

Expressive digital humans with identity retention

Inference is powered by high-performance GPU clusters, supporting real-time response across thousands of concurrent sessions.

Real-Time Content Sync & Moderation

To keep AI twins current with evolving news and market events:

  • Live Data Feed Injection: Daily crawler pulls from X, news APIs, and blockchain explorers.

  • Knowledge Graph Update: Augments the LLM with temporal context.

  • Moderation Stack:

    • Stage 1: Sensitive word filters + response conditioning

    • Stage 2: Factuality checks via trusted source cross-verification

    • Stage 3: User feedback + human-in-the-loop correction pipeline

graph TD
  Crawl[News & Tweet Crawler] --> VectorDB[Real-Time Index]
  VectorDB -->|Augments| LLM
  LLM --> Output
  Output -->|Moderation| Filter
  Filter -->|Final Response| User

KOLI enforces a balance of decentralization and content safety, ensuring avatars are insightful and expressive—yet never harmful or inaccurate.

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