Ghost Terminal Whitepaper

Executive summary of Ghost Terminal - the autonomous AI trading platform powered by WebGPU. Always-on local AI inference, unlimited market observation, and secure wallet infrastructure.

Last updated: January 15, 2026

What We’re Building

Ghost Terminal is an autonomous AI trading platform for the Solana blockchain. At its core is a local AI assistant that runs entirely in your browser using WebGPU—the same technology that powers high-performance gaming graphics, now harnessed for real-time financial decision-making.

Unlike cloud-based AI services (ChatGPT, Claude, etc.), our system doesn’t make requests to external servers for every interaction. The AI model runs on your machine, which fundamentally changes what’s possible.

The Advantage: Always-On, Unbounded AI

Traditional Cloud AI	Ghost Terminal (WebGPU)
Rate-limited API calls	Unlimited local inference
Latency to external servers	Sub-second local response
Periodic polling for updates	Continuous data stream observation
Hourly/daily analysis snapshots	Real-time market awareness
External dependencies	Fully self-contained

What this enables: The AI can observe live market data streams as frequently as we want—every second, every 100ms, continuously—without hitting API quotas or incurring per-request costs. It can synthesize patterns across time windows that would be prohibitively expensive or simply impossible with hosted AI services.

Current System State

What’s Working Now

1. Agent Management Interface

Visual carousel of trading agents with real-time health/status indicators
The primary agent “TOMO” (Spot Trader) is active and configurable
Full parameter control: risk levels, profit targets, stop losses, trade frequency, slippage tolerance

2. Secure Wallet Infrastructure

Military-grade encryption (AES-256-GCM) for private keys
Biometric authentication (Face ID, Touch ID) with password fallback
Multi-wallet support per agent for sophisticated trading strategies
Keys never leave the device unencrypted

3. Living System Architecture

The LLM operates as a finite state machine with defined phases: idle → loading → ready → generating → tooling
Self-healing watchdog that detects stuck states and recovers automatically
Structured telemetry for observability—every decision, every state transition is logged
Backpressure handling: market events queue intelligently, with graceful degradation under load

4. Market Data Integration

Live RxJS streams from market data sources
Bounded event buffers (256 events) with automatic flush cycles
Connector health monitoring with severity grading

Architecture Overview

┌──────────────────────────────────────────────────────────┐
│                    Your Browser (WebGPU)                  │
│  ┌────────────────────────────────────────────────────┐  │
│  │              Local LLM (AI Brain)                   │  │
│  │  • Continuous inference                             │  │
│  │  • Real-time market observation                     │  │
│  │  • Autonomous decision-making                       │  │
│  └────────────────────────────────────────────────────┘  │
│                           │                               │
│  ┌────────────────────────▼───────────────────────────┐  │
│  │              Agent Control Layer                    │  │
│  │  • TOMO (Spot Trader) - Active                     │  │
│  │  • Future agents in development                     │  │
│  └────────────────────────────────────────────────────┘  │
│                           │                               │
│  ┌────────────────────────▼───────────────────────────┐  │
│  │              Secure Execution                       │  │
│  │  • Encrypted wallets                                │  │
│  │  • Jupiter Protocol swaps                           │  │
│  │  • Solana blockchain                                │  │
│  └────────────────────────────────────────────────────┘  │
└──────────────────────────────────────────────────────────┘

What We’re Closing In On

Immediate Horizon

Tool Invocation Loop: The AI can detect when it needs to take action (execute a trade, fetch more data, adjust parameters) and invoke those tools autonomously, then resume its analysis
Continuous Market Awareness: The assistant maintains context across streaming data, building a rolling picture of market conditions rather than point-in-time snapshots

Near-Term

Adaptive Time Budgets: System learns from telemetry to auto-tune how long operations should take
Circuit Breaker Patterns: Intelligent failure handling—trip after repeated issues, require deliberate reset
Multi-Agent Orchestration: Multiple specialized agents working in coordination

The Vision

An AI trading assistant that:

Never sleeps, never misses a market movement
Operates within parameters you set, but with autonomous judgment within those bounds
Runs entirely on your hardware—your keys, your compute, your control
Learns from every market event it observes, building context that cloud services can’t maintain

Key Differentiator

We’re not building a chatbot that you ask for trading advice. We’re building an autonomous agent that watches markets continuously, maintains real-time context, operates within your risk parameters, and acts on your behalf—all running locally with no external AI dependencies.

The WebGPU foundation means we can do what no hosted AI service can: true always-on observation and action, bounded only by the capabilities of the user’s hardware, not by API rate limits or subscription tiers.