Next-Gen Execution Infrastructure

Systematic Trading,
Automated & Scaled.

Engineered by

Quant Researchers

Designed for

Retail Algo Traders

+91
50M+ Executions
99.99% Uptime
strategy_runner.py

import algofarmer as af

# Initialize connection to market data

client = af.Client(api_key="env.ALGO_KEY")

def on_tick(data):

if data.signal == "BUY":

client.orders.market_buy(

symbol=data.ticker,

qty=100

)

[SYSTEM] Listening for webhooks on port 8080...

_

Python SDK
REST API
WebSockets
FIX Protocol
Historical Data

Institutional-Grade Infrastructure

Built from the ground up for quantitative researchers and systematic traders who demand absolute precision.

Ultra-Low Latency

Colocated servers in major financial hubs ensure your orders reach the matching engine before the competition.

Advanced Backtesting

Simulate years of historical tick data in seconds using our distributed computing cluster and accurate slippage models.

Pre-Trade Risk Checks

Hardware-accelerated risk management layers prevent fat-finger errors and strategy runaway without adding latency.

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