Finance

Trade with
Quant Firm Power

The first open-architecture quantitative trading ecosystem. Institutional infrastructure, no walled gardens, no black boxes.

Platform

Core Capabilities

01

Visual Strategy Builder

Build sophisticated trading algorithms without writing boilerplate. Drag-and-drop for speed, or inject custom Python/JavaScript nodes for infinite flexibility. Live debugging lets you inspect logic flow in real-time.

02

Machine Learning & Reinforcement Learning

Deploy frameworks used by top quant firms—TensorFlow, PyTorch, Stable-Baselines3. Use RL agents to discover novel strategies with automated hyperparameter tuning via Optuna.

03

Institutional-Grade Backtesting

Event-driven engine simulates decades of market data in minutes, accounting for slippage, transaction costs, and order book depth. Test 10,000 strategy variations in a single weekend.

04

Open Microservices Architecture

Built on 13 independent, containerised microservices. Run only what you need. Deploy via Docker on your local machine, AWS, or private VPS. Full REST and WebSocket APIs.

05

Satellite Guided Inference

Harness alternative data streams from orbital imagery. Track retail foot traffic, shipping activity, and agricultural yields in real-time. Computer vision pipelines transform raw satellite feeds into actionable trading signals.

Comparison

The Ziro Advantage

FeatureTraditional RetailZiro Finance
Strategy CreationLimited scriptingFull Python/JS + Visual Builder
AI/MLNon-existent or black boxFull TensorFlow/PyTorch
Data AccessProprietary, locked-inOpen APIs
InfrastructureShared, high latencyPrivate Docker, low latency
Testing CostHigh (live required)Zero (backtesting)

Applications

Built For You

For the Data Scientist

Your analysis deserves institutional-grade infrastructure. Deploy explainable deep learning models with full auditability, no more black boxes. Focus on alpha generation while we handle the engineering complexity.

For the Developer

Build trading systems the way you build software. Clean abstractions, version control, CI/CD pipelines, and observability built in. Your engineering discipline finally applies to financial markets.

For the Discretionary Trader

Codify decades of pattern recognition into systematic strategies. Backtest against historical regimes, stress-test against black swan events, and execute with mathematical precision while preserving your intuition.

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