Case Studies

Delivered Solutions

A selection of trading infrastructure projects we have designed, built, and deployed for institutional clients.

01
Trading Automation

Multi-Broker Indian Equities Automation Engine

A unified execution layer connecting multiple Indian brokers for automated equities and derivatives trading with smart order routing.

The Challenge

The client operated across three Indian brokers with different APIs, order formats, and latency characteristics. Manual order entry across platforms caused execution delays and increased operational risk. Position reconciliation required hours of daily manual effort.

Our Solution

We built a unified order management system with broker-specific adapters for Zerodha, Angel One, and IIFL. The system includes smart order routing based on available margins and broker-specific execution quality, automated position reconciliation, and a real-time monitoring dashboard.

Technologies Used

PythonFastAPIZerodha Kite ConnectPostgreSQLRedisReactDocker

Key Outcomes

  • Order execution time reduced from minutes to under 200ms
  • Daily reconciliation automated — saving 3+ hours per day
  • Supports 500+ orders per day across three brokers
  • Zero manual intervention required for standard operations
02
Crypto Infrastructure

Cross-Exchange Crypto Arbitrage Infrastructure

A low-latency arbitrage system monitoring price discrepancies across centralized exchanges with automated execution.

The Challenge

The client needed to capture price discrepancies across multiple crypto exchanges in real-time. Existing tools lacked the speed and reliability needed for consistent execution, and manual monitoring was impractical across 20+ trading pairs.

Our Solution

We deployed a containerized system with dedicated WebSocket connections to five exchanges. The engine continuously monitors order books, identifies opportunities based on configurable thresholds, and executes simultaneously on both legs with pre-funded accounts.

Technologies Used

Node.jsRustBinance APIWebSocketsRedisDockerAWS

Key Outcomes

  • End-to-end detection-to-execution latency under 50ms
  • Monitors 20+ pairs across 5 exchanges simultaneously
  • 99.7% uptime over 12 months of continuous operation
  • Automated inventory rebalancing across exchanges
03
Algorithmic Trading

Options Scalping Execution Platform

A high-speed options trading platform with configurable scalping strategies for index options on NSE.

The Challenge

The trading desk needed a system capable of rapidly entering and exiting index options positions based on real-time Greeks and underlying price movements. Existing platforms introduced unacceptable latency in the order placement workflow.

Our Solution

We developed a dedicated execution platform with real-time options chain monitoring, computed Greeks, and a configurable strategy engine for scalping. The system pre-computes order parameters and uses direct API connections for minimum-latency execution.

Technologies Used

PythonRustZerodha Kite ConnectWebSocketsRedisReact

Key Outcomes

  • Order placement latency reduced to under 100ms from signal
  • Real-time Greeks computation across full options chain
  • Configurable risk parameters with automatic position sizing
  • Handles 200+ round-trip trades per session
04
HFT Infrastructure

Cross-Exchange Market Making System

An automated market making system providing liquidity across multiple crypto exchanges with dynamic spread management.

The Challenge

The client needed to provide continuous liquidity on multiple crypto exchanges while managing inventory risk and adapting to changing market conditions. The system had to operate 24/7 with minimal human oversight.

Our Solution

We built a market making engine with dynamic spread computation based on volatility, inventory position, and exchange-specific fee structures. The system continuously quotes on both sides, manages inventory through cross-exchange hedging, and adjusts parameters based on real-time market conditions.

Technologies Used

RustPythonWebSocketsRedisPostgreSQLDockerKubernetes

Key Outcomes

  • Continuous quoting with 99.9% uptime
  • Dynamic spread adjustment based on 15+ market features
  • Automated inventory management across 3 exchanges
  • Real-time P&L and risk monitoring dashboard
05
Analytics & Research

AI-Assisted Portfolio Analytics Dashboard

A comprehensive portfolio analytics platform with ML-driven insights, risk decomposition, and automated reporting.

The Challenge

The fund manager needed a unified view of portfolio performance across multiple strategies and asset classes. Existing tools provided fragmented data without actionable insights, and monthly reporting consumed significant analyst time.

Our Solution

We built a web-based analytics dashboard that aggregates data from multiple trading systems and provides real-time performance attribution, risk decomposition, and ML-driven anomaly detection. The system auto-generates client reports with configurable templates.

Technologies Used

Next.jsPythonFastAPIPostgreSQLTradingViewD3.jsscikit-learn

Key Outcomes

  • Unified view across 8 strategies and 3 asset classes
  • Automated monthly reporting — reducing analyst time by 80%
  • ML-based anomaly detection with configurable alert thresholds
  • Interactive performance attribution down to individual trade level

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