Multi-broker integration
One unified layer over Interactive Brokers, MetaTrader, Exante and FIX, with accounts and feeds synchronized in real time.

Complete engineering, from market infrastructure through to execution, designed, deployed and operated in production for demanding institutions.
Brokers, accounts and market feeds brought together in a unified platform and synchronized in real time, from Interactive Brokers to MetaTrader, Exante and FIX.
Algorithmic execution engines, position replication and rigorous backtesting, from signal through to the order sent to market.
Market-data infrastructure, institutional-grade analytics and machine-learning models in the service of decision-making.
Dashboards, real-time APIs and continuous monitoring give you complete, auditable control over your entire operation, around the clock.
Our technology stack






Concrete systems we design, ship and run, each proven in production across our managed accounts.
One unified layer over Interactive Brokers, MetaTrader, Exante and FIX, with accounts and feeds synchronized in real time.
Execution engines and order management, from signal to the order sent to market, with retries and full logging.
The same high-performance engine in research and production, so a strategy goes live only once its edge is proven.
Minute-level OHLCV collection, gap back-filling and real-time WebSocket streaming with built-in indicators.
Trader-facing web apps and desktop control panels for complete, auditable oversight of every operation.
Heartbeat monitoring, crash detection and 24/7 alerting via Telegram and email keep everything running.
From multi-broker integration to end-to-end backtesting, a selection of systems we have designed, deployed and operated in production.
We designed a centralized platform that integrates five major brokers (Interactive Brokers via the TWS API, MetaTrader 5, MetaTrader 4, Exante via the FIX 4.4 protocol and Velocity) and manages over 60 trading accounts in production. Positions, balances and margins are synchronized in real time through a single abstraction layer, delivering consistent operational control regardless of the underlying broker.
We designed and built the full trader-facing web application on top of our platform, a modern React + TypeScript single-page app, styled with Tailwind and powered by real-time charting. From one interface, users monitor every connected brokerage account, supervise running strategies, inspect trades, manage rebates and export PDF and Excel reports in a click. It ships as an installable Progressive Web App with offline-ready service workers and token-based authentication, a professional cockpit for desktop and mobile.
We built a framework for running automated strategies. Each algorithm is configured in the database with its parameters, instruments and target timeframe (M1 to D1). The engine routes orders to the designated accounts, handles simultaneous multi-symbol deployment and switches between live and backtest modes.
We built an automatic trade-replication engine between accounts. A master account broadcasts its positions to multiple slave accounts among the 60+ we manage. Granular rules drive every copy, from filtering by symbol or asset class to a 'close-only' mode and hot enable/disable. Execution is hardened by automatic retries and full logging of each operation.
Every hour, we retrieve the latest Bitcoin price data. Our deep learning model, after meticulous data preprocessing, performs an inference on the projected direction of Bitcoin's value for the current hour. The prediction results, along with their confidence level, are then integrated into our trading algorithms. They provide crucial insights to inform real-time strategic decisions.
Every strategy we develop goes through the same rigorous backtesting pipeline before it touches a live account. We pull years of tick-level history from our PostgreSQL market database and replay it through the very same high-performance Go engine that runs in production. Each run yields trade-by-trade results, risk-adjusted metrics and an interactive TradingView visualization of every signal, entry and exit, so research matches live execution and a strategy is promoted to real capital only once its edge is proven.
Optimizing input parameter combinations for a trading strategy using Metatrader 5 tools can take hours depending on its complexity. With our custom-made deep learning model, over 100,000 combinations can be processed in less than a second, reducing optimization time by a factor of 10 to 100. This substantial time-saving is invaluable, especially for strategies requiring frequent updates.
We developed an institutional-grade trading statistics module that automatically computes Sharpe, Calmar, Profit Factor, Win Rate, MAE/MFE, maximum drawdown, AHPR and GHPR. It produces performance curves (balance, equity, drawdown, daily P&L) broken down by symbol, account and broker, along with monthly tracking of rebates and commissions.
We collect and store minute-level OHLCV data for every traded instrument, with automatic detection and back-filling of historical gaps. Data is streamed in real time over WebSocket in the TradingView Lightweight Charts format, with built-in technical indicators (RSI, EMA, MACD), all backed by PostgreSQL connection pooling.
We expose the full feature set through a FastAPI service secured by API key, covering accounts, positions, order placement, performance statistics, market data and copy rules. Position updates are streamed over WebSocket at 300 ms, with per-portfolio access control and action logging for audit.
We continuously monitor every process through a heartbeat mechanism, with automatic crash detection and restart. Alerts are delivered in real time via a Telegram bot and email (Azure Graph API), covering executions, errors, account disconnections and unfilled orders.
We developed a PyQt6 desktop application that gives a complete overview of every platform service. It provides individual control of each broker (start/stop), real-time status indicators and one-click launch of backups and alerts. The whole application is designed for day-to-day production operations.
Using MT5 Manager, monitoring account performance in real time, recording the data and computing key metrics. This was used for a Prop Firm to monitor trading challenge completion using C++. The data is monitored with a single digit latency and the program is implemented through a Windows Server virtual machine.
We have built a whole copy-trading solution, including a web interface for each user to track their performance for each strategy. The project was built using Google Cloud Platform and includes a secure database, a web interface, several endpoints, as well as an engine to send trade signals to Binance through its API. By controlling every step of the process, we ensured our solution was the most suitable for this project.
We implemented an order-queue architecture to open, close and modify TP/SL asynchronously. Requests are persisted to the database, then processed in the background by the relevant broker process. Every request carries a unique identifier, a processing status and an error history, tracked by polling with a timeout, for end-to-end traceability.
We orchestrate multi-broker backups in parallel, from IBKR statements via Flex Query to multi-terminal MT5/MT4 sessions and Exante and Velocity archiving. The full history (trades, positions, balances, equity) of the 60+ accounts is retained for over 24 months in PostgreSQL, enabling retrospective analysis and long-term trend tracking.
Want to get the latest info right to your mailbox, Discord or Telegram channel? Monitor key indexes changes to always be up to date when something happens. These projects have been built using Google Cloud Platform. The monitoring algorithms are made with Python and run 24/7 through a Linux virtual machine. We can send notifications through email, Discord, Telegram and more.
A disciplined path, from understanding your operation to running it in production, end to end.
We map your trading operations, brokers, data and constraints to define exactly what to build.
We architect the systems, infrastructure and integrations, and agree the success criteria upfront.
We engineer and rigorously backtest every component before it ever touches live capital.
We deploy, monitor and run the systems in production, end to end, around the clock.






