All case studies
High-Frequency Trading · Web3

BigAl Sniper Bot

A low-latency Solana trading bot engineered for sub-200ms transaction construction. AWS EC2 with CPU pinning, Rust transaction builder, Jito bundle submission, and a real-time terminal UI.

Year
2026
Tech Stack
RustSolana SDKJito BundlesPython (orchestration)WebSocketsReact (terminal UI)AWS EC2 (us-east-1)
The Problem

What we set out to solve.

On-chain memecoin launches resolve in milliseconds. Off-the-shelf trading clients add network hops, garbage-collected runtimes, and shared-tenant CPU contention that put any retail bot a tick behind. Latency is the entire alpha.

Our Approach

How we built it.

01

Hot path in Rust

The transaction builder is written in Rust with statically allocated buffers and zero heap churn on the hot path. Signing keys live in memory; instruction layouts are precomputed at startup.

02

CPU pinning and EC2 placement

The bot runs on an EC2 instance in us-east-1 (Jito region), with the executor pinned to a dedicated physical core via taskset. The Python orchestration layer runs on separate cores so it cannot preempt the hot path.

03

Jito bundling

Submitted transactions ship as Jito bundles with tip configuration tuned per launch profile. WebSocket dashboard streams every signed bundle, slot landing, and PnL in real time to a Fidelity-inspired terminal UI.

Results

The numbers.

31%
Hot-path latency improvement
< 200 ms
Transaction build time
Region-leading
Bundle land rate
Outcome

What it changed.

A vertically integrated trading stack — from market data ingest through signed transaction land — that competes on the same latency floor as professional desk infrastructure, controlled from a single browser-based dashboard.