Institutional Grade

Quantitative Trading
Reimagined for the Institutional Era

AI-native execution across equities, options, and futures. Multi-instance architecture with real-time portfolio hedging, designed for hedge funds, family offices, and professional trading desks.

+2.91%
30D Portfolio Alpha
10,000+
Executed Trades
4
Engine Instances
99.7%
Uptime
Deploy Anywhere

One Platform, Every Device

Monitor, execute, and manage from desktop, mobile, or tablet. Consistent experience across macOS, iOS, and Android — all connected to the same real-time engine.

macOS Desktop

Native Swift app with WKWebView dashboard, auto-update via GitHub Releases, and direct engine connectivity.

macOS 13+ GitHub

iOS

Face ID/Touch ID auth, push notifications for trade alerts, WKWebView rendering with OTA distribution.

iOS 16+ · App Store Ready

Android

Jetpack Compose UI, biometric authentication, Firebase push notifications, and direct APK distribution.

API 31+ · Play Store Ready
Engine & Infrastructure

Institutional-Grade Infrastructure

Purpose-built for serious capital. Multi-engine architecture, cloud-agnostic deployment, and real-time risk management — all in one integrated system.

Multi-Instance Engine

Run up to 4 isolated engine instances simultaneously — live trading, paper accounts, and micro strategies — each with independent config and risk parameters.

Real-Time Position Sync

Atomic state file writes with sub-second dashboard updates. Every position, P&L delta, and market data change is reflected instantly across all connected clients.

Cloud-Agnostic Deployment

Deploy to Azure, AWS, GCP, or on-prem Linux servers with a single YAML spec. Generate Terraform, CloudFormation, or Docker Compose manifests automatically.

State Persistence & Recovery

SQLite-backed trade ledger, reasoning memory in JSONL, atomic file writes. Engine crash recovery with automatic state restoration on restart.

Multi-User & Role Isolation

Engine instances can be assigned to different accounts or team members. Isolated configs, token files, and P&L tracking per instance — no cross-contamination.

Enterprise Security

OAuth 2.0 broker authentication, biometric app locks, encrypted credential storage, Cloudflare DDoS protection, and TLS everywhere — defense in depth.

Architecture

How AI-QUANT Operates

From market signal to trade execution — a look at the real-time pipeline powering every decision.

1

Market Signal

C++ engine ingests real-time quotes via Schwab API, runs HMM regime detection and volatility analysis continuously.

2

Reasoning Engine

Multi-factor decision matrix evaluates signal strength, portfolio delta, and risk constraints before generating an order intent.

3

Execution

Orders are routed through the broker API with position sizing and exit conditions pre-attached. Every fill is logged to the trade ledger.

4

Dashboard Sync

State is atomically written and pushed to all connected clients — desktop, iOS, Android — in real time via the Nginx reverse proxy.

Interactive Demo

Agent Command Center

See how institutional traders interact with AI-QUANT in natural language. Every command triggers real hedging logic, exposure adjustments, and risk analysis — all in real time.

⚡
AI-QUANT Agent
Engine Instance · latency 12ms
Live
ai-quant-engine — bash — 80×24
honeypotz@ai-quant:~$ enginectl status --instance prod-01
● engine-prod-01 active PID 28491 uptime 14d 7h mem 2.3GB/8GB
honeypotz@ai-quant:~$ hedge --portfolio P7 --delta-target 0.15
[OK] Scanning 12 positions…
Ready for commands…
Portfolio Delta
0.48 —
Live Market LIVE
SPY——
QQQ——
NVDA——
AAPL——
VIX——
Open Positions
12
5 long · 3 hedged · 4 neutral
Margin Utilization
34%
P&L (Session)
+$18,420
256-Bit Encryption
Sub-100ms Latency
SOC 2 Ready
Cloud-Agnostic
4-Nines Uptime
10,000+ Executed Trades
Live Dashboard

Command Your Portfolio

Institutional-grade dashboard with real-time P&L, risk decomposition, and one-click hedging — on desktop or mobile.

Portfolio Overview — ai-quant engine v3.2
Positions
SPY400 Shares$232.9K+$3,420
QQQ250 Shares$123.2K+$5,410
NVDA600 Shares$82.9K-$2,150
SMH150 Shares$38.6K+$1,180
AAPL200 Calls$14.2K+$820
P&L Sparkline (Session)
09:3016:00
Risk Metrics
Delta 0.58
VaR 95% $47.2K
Sharpe 1.42
Marg% 34%
Exposure
0%Target 60%100%
AI-QUANT ● LIVE
$2,102,420
+$18,420 (0.88%)
9:3016:00
Portfolio Delta
0.58x
Positions
12 open
Margin Utilized
34%
Hedge
+Size
Risk
Common Questions

Frequently Asked

Who is AI-QUANT built for?

Institutional traders, hedge fund managers, family offices, and quantitative portfolio managers who need multi-instance execution with real-time hedging capabilities across equities, options, and futures.

What brokers are supported?

The platform integrates with Schwab's OAuth 2.0 API for order execution and market data. Additional broker integrations are on the roadmap based on institutional demand.

Can we deploy on-premises?

Yes. The full stack — engine, dashboard, and Nginx proxy — can be deployed on any Linux server via Ansible or a single shell script. No cloud dependency required.

How does hedging work?

AI-QUANT uses a multi-factor decision matrix that continuously evaluates portfolio delta, sector exposure, and volatility regimes. Exit conditions are pre-attached to every order at entry.

Is there a mobile app?

Native iOS and Android apps provide real-time dashboard access, push notifications for trade alerts, biometric authentication, and engine instance management — all from your phone.

How do I get started?

Request access below. Our team will walk you through deployment options, broker configuration, and an initial strategy calibration. No self-serve signup — every deployment is provisioned with institutional diligence.

Get Started

Ready to Move Beyond the Ordinary?

AI-QUANT is available to qualified institutions, professional traders, and family offices. Every deployment is provisioned with personal onboarding.

Customer Service — aiquant@honeypotz.net · +1 (203) 273-2101 · 24h response SLA for institutional clients