The platforms, brokers and languages we build on
From retail brokers to institutional OMS/EMS systems, every entry in the main lists is something we've built for, not a logo we found. Where we can integrate but haven't shipped production work yet, we say so plainly in a separate list below. We don't blur “built for” into “compatible with”.
Trading platforms & software
Institutional OMS / EMS
US & global brokers
India brokers
Asia-Pacific brokers
Crypto venues
Languages & protocols
Market-data feeds
We can also integrate these — on request
Platforms and venues we have the capability to integrate but have not shipped production work on yet. We'd rather tell you that plainly than pad a list.
Language-agnostic, on purpose
We're not a “Python shop” or a “C++ shop”. Python for research and most execution; C++ when you need microseconds; C# for NinjaTrader; Java for enterprise systems; MQL5 for MetaTrader. We pick the right tool for your platform and latency budget. Python is where most people start, and it's what our custom software work most often uses, but it's a doorway, not a limit.
If you are starting out, our guide to building a trading bot in Python walks through the basics end to end.
Data is a decision, not a default
The feeds above range from broker-provided data to premium tick sources like Nanex and IQFeed. Which one your strategy needs is a real question with a real cost attached, and often the honest answer is “less than you think”. We go into that on the market-data engineering page, including when a strategy genuinely needs tick-by-tick data and when a broker feed is fine.
Architecture is a decision too
The same honesty applies to the infrastructure a system runs on. Some strategies need serious, low-latency hardware; most run cheaply on ordinary cloud. We match the architecture to the workload, so you are not paying for speed you never use. More on the trading system architecture and infrastructure page.