Investor-ready longform context for AIQuant Lab
A readable web-native whitepaper outlining the problem, architecture, infrastructure, security model, economics, and roadmap.
Executive Summary
AIQuant Lab is a non-custodial AI trading infrastructure platform built for DEX execution. It combines machine learning, execution routing, and quant supervision into a single capital operating layer.
The product is designed to reduce manual complexity while keeping the user in control of custody, allocation, and risk acknowledgements.
Problem
Most crypto automation tools either force users into manual bot configuration or hide risk behind marketing-heavy dashboards.
AIQuant Lab addresses this gap with AI-guided deployment, explainable activity, and source-labeled performance reporting.
Technology
The platform blends market microstructure analytics, on-chain flow analysis, and AI regime classification to drive timing and allocation recommendations.
Execution policies are supervised with venue health checks and user-selected risk boundaries.
Infrastructure
Inference and scenario testing are built on GPU-backed infrastructure aligned with NVIDIA H200, B300, and GB300 class compute capacity.
The system prioritizes execution continuity, observability, and rapid scenario evaluation.
Security
AIQuant does not custody assets, store withdrawal authority, or present trading outputs as financial advice.
Permission requests are human-readable and limited to approved trading actions on supported venues.
Revenue Model
The launch model is performance-fee driven, aligning platform revenue with user outcomes while keeping fee policy transparent and auditable.
Roadmap
Phase 1 focuses on AI-guided onboarding, DEX integrations, explainable strategy execution, and referral-led growth.
Later phases expand into saved scenarios, institutional multi-wallet support, and marketplace-style strategy distribution.