Institutional-grade autonomous trading, delivered as a service
HedgeVision is a fully autonomous, multi-asset algorithmic trading platform engineered for institutional-scale operation. It fuses statistical inference, machine learning, and LLM deliberation into a single unified execution system — running continuously, 24/7, without manual intervention.
It is not a research sandbox or a backtesting harness. It is a production trading platform built on principled software architecture and delivered as a fully managed cloud service — so you can focus on strategy, not infrastructure.
What HedgeVision Is Not
- Not a retail trading app or consumer product.
- Not a backtesting harness or research sandbox.
- Not a black-box signal service with no visibility.
- Not a DIY toolkit that requires your own DevOps team.
- Not an educational demo or toy project.
HedgeVision is designed for funds, prop desks, and sophisticated traders who need production-grade infrastructure without the engineering overhead.
Design Principles
Defensible decisions, not black-box outputs
Every trade carries a structured narrative — debate notes, adversarial critique, chaos simulation output, red team result — all attached to the order record.
Trust-but-verify at every layer
Statistical models are cross-checked by ML models, ML outputs are critiqued by LLMs, LLM suggestions are vetoed by reality checks (SanityGuard) and adversarial agents (RedTeam).
Fail safely, not silently
Circuit breakers trip on drawdown, failure rate, and latency. The system defaults to paper trading when broker connectivity fails. Stale human approvals are auto-rejected after 15 minutes.
Architecture for longevity
Domain-Driven Design (DDD) with Ports & Adapters (Hexagonal Architecture) throughout. Null Object patterns ensure graceful degradation. Every sub-system can be replaced or upgraded independently.
Technology Stack
| Layer | Technology |
|---|---|
| API Server | Python 3.12+, FastAPI, Uvicorn (async) |
| Time-Series Database | TimescaleDB (PostgreSQL 17 + time-series extension) |
| Cache / Pub-Sub | Redis 7 (1 GB LRU cache, pub/sub queues) |
| Scheduler | APScheduler AsyncIOScheduler (UTC, 20 jobs) |
| ML Framework | AutoGluon, XGBoost, LightGBM, PyTorch (CPU), stable-baselines3 |
| LLM Orchestration | LangChain, LangGraph (StateGraph), multi-provider fallback chain |
| RL Agent | PPO via stable-baselines3, gymnasium environment |
| Broker Connectivity | CCXT (Binance), ib-insync (IBKR), REST bridge (MT4) |
| Cloud Infrastructure | Kubernetes, auto-scaling, multi-region failover |
| Monitoring | Prometheus, Grafana, Sentry, New Relic APM, real-time alerts |
| Experiment Tracking | MLflow |
Security & Compliance
HedgeVision infrastructure is SOC 2 compliant with end-to-end encryption at rest and in transit. Broker API credentials are stored in hardware-backed secret management. Every access is logged and auditable.
Your trading data and strategies remain fully isolated — multi-tenant architecture with strict data boundaries ensures no cross-client data leakage. We never access, share, or monetize your trading signals or portfolio data.
Ready to get started?
HedgeVision is available as a fully managed cloud platform. Connect your broker, configure your risk parameters, and start trading — no infrastructure setup required.