Transforming data into decision making trades. An all‑in‑one ecosystem bridging institutional‑grade Tools and retail innovation.

📧 Investor Relations
$2.5 MValuation
$250 KPre‑Seed Raised
6Core Engineers

In‑House Fund

Multi‑Agent RL Engine

A hierarchy of adversarial reinforcement‑learning agents compete for capital allocation, ensuring only top‑performing strategies execute live.

  • Sub‑500 microsecond CME execution
  • Real‑time self‑adaptive hyper‑parameter tuning
  • Risk‑on/off governor with latency arbitrage filters

Q Library

Proprietary Python/C++ micro‑structure library powering both fund & retail products.

  • Tensor‑parallel clustering + Graph attention nets
  • Simulated limit‑order‑book environments
  • Plug‑in alpha modules for researching

Performance Flywheel

Fund revenues subsidize R&D, feeding features directly into retail tools—compounding innovation across the ecosystem.

  • 10% net PnL reinvested into retail GTM
  • Shared data lake accelerates model training
  • Alpha conversion metrics tracked end‑to‑end

In‑House Fund Roadmap

April 25

$250K Secured

Apr – May

Model Training

May – Jun

Testing Phase

June 25

Live Deployment

June-Milestones

Live Demo Milestone

Our first live demo achieved an 82% win rate, showcasing precision execution and high-frequency alpha capture on volatile assets.

  • NQ Scalping Experiment Executed a controlled NQ scalp strategy yielding over 100 points within 30-minute windows—demonstrating real-time model adaptability and liquidity awareness.

Order Engine Architecture

Jonathan and Vedant engineered a dynamic order routing system—built for latency reduction, conditional logic, and adaptive risk management.

  • Rithmic API- Jonathan and Vedant built a modular order placement framework using the Rithmic API, fully integrated with the Quantegies ML Development Library for seamless execution.

Accelerated Model Training

Using a advanced data structure, Jonathan and Vedant accelerated training models—boosting performance from 3% to 40% in just one week, enabling near real-time reinforcement cycles.

  • Parametric Training Loop- Enables rapid iteration and testing across varied configurations to accelerate development of high-performing models..

Retail Product Suite

Q Journal

AI‑driven trade journal with human‑like insight & community marketplace.

$25 / yr
  • Unlimited accounts & broker APIs
  • Personalised agent analysis
  • Backtesting & optimizer lab
  • Strategy & Learning marketplace

Q Flow

Real‑time order‑flow intelligence with AI anomaly detection.

$299 / yr
  • Live liquidity heat‑maps
  • Spoof & stop‑hunt alerts
  • Unusual order clustering
  • Proprietary RL signal engine

Trade Controllers

Physical & digital risk keyboard for one‑click execution & account lockouts.

$79.99 one‑time
  • Broker‑agnostic hot‑key pad
  • Auto risk‑bracket presets
  • Over‑trading lock switch
  • Companion desktop app

Retail Roadmap

June 25

Q Journal Release

Aug 25

Q Flow Release

Sept 25

Trade Controllers Release

Meet the Quantegies Team

Saif Ismail
CEO
Jonathan Stephens
CTO
Vedant D.
Backend Engineer
Yash W.
Full‑Stack Engineer
Andrew J.
Front‑End Engineer
Zac M.
Q Journal Lead
Tanishq A.
Backend Engineer
Eram K.
Frontend Engineer
Yash A.
Full-stack Engineer

Investor Partnership Roadmap

Beyond capital, we value partnerships that catalyze shared growth.

Step 1

Initial Consultation

Step 2

Due Diligence

Step 3

Strategic Partnership
🤝 Partner Up