Independent Audit
Performance and calculation methods will be audited and certified by an independent third-party auditor upon the official launch of the platform.
LITL • Security & Compliance
Compliance & Operation
This page transparently describes how LITL operates legally and technically: independent audit, non-custodial architecture, regulatory framework, API security, and no guarantee of returns.
Non-Custodial Solution
We never hold user funds. The money remains exclusively in their personal Bybit/Binance account. We do not have the ability to transfer, block, or withdraw funds without the user's action.
A Technological SaaS (Non-Financial)
LITL is a trading automation software, serving as an intelligent interface between the market and the user's Bybit/Binance account. We do not offer investment advice or regulated portfolio management.
Regulatory Scope & MiFID II
LITL is designed as a non-custodial SaaS software and is not intended to provide regulated investment services as defined by the European MiFID II directive. The platform does not hold user funds, does not provide personalized investment advice, does not manage portfolios on behalf of clients, and does not execute any orders in its own name.
As such, LITL does not present itself as an investment services provider, but as a technological tool that the user controls under their own responsibility, via their own Bybit/Binance account. Each user remains fully responsible for their decisions regarding market exposure and may seek independent financial or legal advice if they wish.
Secure Connection to Bybit/Binance
Each user, when creating a LITL account, will have a Bybit/Binance account opened in their name, giving them full access to deposit or withdraw freely. The AI acts only through trading API permissions (trade only, never withdrawal).
Neuronal Artificial Intelligence & Simulations
LITL relies on artificial intelligence models based on neuronal networks trained on vast historical datasets, enriched by millions of simulated scenarios. These models analyze market sequences, detect statistical patterns, and evaluate high-probability configurations.
Despite this considerable volume of training, the decisions generated by the AI remain probabilistic and uncertain. Simulations, backtests, and stress tests improve the robustness of the algorithms but do not constitute any guarantee of future performance.
No Guaranteed Returns
No returns are guaranteed. Past performance does not predict future results and does not constitute a promise of gains.