Phoenix Quant

We just reached a milestone at Phoenix Quant: an internal working version of live market analysis in Discord, powered by Signal Fury’s Omega Shadow LLM (“Omega”).

What it does:
Posts simple, structured outlooks: current price, key levels, and bull / base / bear paths when asked.

Highlights risk lines (where things break) so you know what could go wrong.

Lives right in Discord, so you see analysis where you already chat.

What this means for you:
Less time parsing charts, more time understanding the plan.

This is just the base case, the LLM is a live chat assistant for the community. Just ask "Hey Omega" and begin to recieve clear scenarios you can compare to your own view.

When we go live, this will sit beside our OMS/EMS so protections can be set fast. This is not available yet. We plan at least six months of real-world testing and are aiming for early 2026 for public availability.

Educational content only; not investment advice.

Here’s a snapshot from today’s system test:
• The platform ran hundreds of trades in a controlled environment.
• Wins outweighed losses by a clear margin.
• The system closed the day positive, showing stable ex*****on and reporting.

The point isn’t just the numbers, it’s that the OMS/EMS can handle ex*****on, compliance, and reporting in sync, while giving a transparent view of performance.

Six months of real-world testing will help validate this before launch in early 2026.

Today we tested our OMS/EMS routing across multiple broker platforms and accounts.
• Trades were opened, modified, and closed in real time.
• FIFO rules were enforced for U.S. forex brokers.
• Results posted simultaneously into Discord channels.

This shows how the platform can coordinate ex*****on across venues while maintaining compliance and delivering transparent signal distribution.

We started with a goal of 1-second ex*****on.
This capture shows multiple trade actions—order fill, stop loss, and take profit—processed in under one second through the OMS and EMS.

Beyond speed, each trade also feeds into Omega Shadow, the AI layer that learns from ex*****ons in real time. While traders can add stops manually at a broker, this system enables advanced cases: trailing stops, moving targets, and adaptive trade management—executed nearly instantly.

Latency matters, and this shows what’s possible. Our goal is to complete at least six months of real-world testing before launching in early 2026. 🐦‍🔥

We test using live data, and real money so the models can train based on real world market conditions. — Broker: OANDA

Testing the webhook ingress traffic, our bridge assigns 202 with low latency (sub 200ms) for acceptable urls. The images display 202 for multiple brokers, accounts, and multiple assets. (Oanda-Forex and Alpaca-Crypto)

Source: ngrok

In development,
We’ve developed a quant engine that trades forex, crypto, and equities OMS that auto creates alerts in the market via Trading View’s platform. Also, we’ve developed an EMS that routes these signals to any broker, on any platform.

This allows any strategy to trade with automated ex*****on using Trading View with webhooks and APls to any broker.

*The model trades the EUR/USD perfectly in this market example, all plotted and executed automatically. Think Zaiper but for trading ⏳

- COMING SOON