Infrastructure Deep Dive
12+ months of engineering, LP negotiations and infrastructure build — this is what separates a strategy that runs in production from one that runs in a backtest.
Every trade travels through a purpose-built institutional execution chain before reaching liquidity
MT5 serves as the execution engine for our proprietary AI algorithms. Custom MQL5 code interfaces with institutional infrastructure — far beyond standard retail MT5 usage.
The critical translation layer between MetaTrader's proprietary protocol and the institutional FIX ecosystem, where retail solution ends and institutional execution begins.
The institutional aggregation layer between our FIX Bridge and the LP network. Handles smart order routing, LP stream aggregation and real-time best execution logic.
Outbound FIX connections to each liquidity provider — the same protocol used by tier-1 prime brokers globally. Dedicated sessions per LP with isolated failover.
Not all LPs are equal. Finding providers comfortable with our execution profile took months of live testing, spread analysis and negotiation. 50+ tested, ~20 retained.
Real-time monitoring across the full stack — from EA-level position limits to LP-level fill quality. Live visibility into every account and execution metric.
What it actually took to build an institutional execution stack from scratch
Establishing a working relationship with Metaquotes to access institutional-grade MT5 server infrastructure and FIX Bridge documentation. Custom EA development and adaptation for low-latency institutional execution.
PrimeXM account setup, FIX Bridge integration and initial LP stream configuration. Extensive testing of order routing logic, fill quality at different lot sizes and latency profiling across instruments.
Identifying liquidity providers willing to sustain our execution profile without progressive spread widening or flow toxicity rejection. Tested 50+ LPs in live conditions. Retained ~20 that met fill quality and tolerance criteria.
Adapting ML/RL algorithms to the production execution environment accounting for real-world latency, partial fills and LP-specific execution characteristics. First live client account: April 2024.
This infrastructure cannot be replicated in weeks. The combination of Metaquotes relationships, PrimeXM configuration expertise and a curated LP network tolerant of our execution profile represents a full year of work and institutional relationships that are not publicly available.
Any partner integrating with this stack inherits a production-ready institutional execution layer — not a demo environment.
Result after 25 months live
Every architectural decision was made with capacity in mind from $54k to $500M+
The $50M figure comes from LP depth analysis across our ~20 providers at current execution sizes. Beyond that threshold, queue positioning deteriorates and spread widening becomes measurable on XAUUSD and indices during peak sessions. This is a live observation from production data — not a model assumption. The tier-1 PB onboarding roadmap is specifically designed to add depth at that transition point.
Institutional execution infrastructure is not a commodity each element required time, relationships and iteration
Direct working relationship for FIX Bridge access and institutional MT5 server configuration — not available through standard channels.
Months of live tuning of routing logic, LP stream weighting and fill quality parameters institutional knowledge embedded in the config.
~20 LPs selected from 30+ tested in live conditions for tolerance to high-frequency directional flow. These relationships are not publicly replicable.
Algorithms adapted to this specific execution environment latency, partial fills, LP-specific behaviour. That adaptation is not portable to generic infrastructure.
$54k $714k single account, $7.6M total AUM — execution quality validated at increasing scale in live conditions, not modelled.
Signal generation, execution, risk monitoring and reporting in one integrated stack — no dependency on third-party black boxes at any critical layer.
The next evolution: a fully autonomous institutional trading system
The next evolution of this infrastructure is full autonomous operation a Dark Factory model where the entire stack runs without human intervention (almost). Signal generation, execution, risk management and reporting operate as a self-managing agentic system 24/7.
We are integrating Archon OS — an open-source agentic AI framework (13.7k+ GitHub stars) — as the knowledge and task management backbone. Archon orchestrates AI agents across the full trading pipeline: strategy monitoring, anomaly detection, LP performance alerts and autonomous parameter adaptation.
The result: a fully autonomous institutional trading system that self-monitors, self-optimises and self-reports — with human oversight reserved for strategic decisions only.
We are building Nexus Fund with the right institutional partner. If you understand what this infrastructure represents let's talk.