BoltSniper AI – Serverless Trading with Smart AI

is a ultra-low-latency trading bot powered by AWS. It uses AI to validate signals in real time, executes scalping strategies securely, and dynamically manages TP/SL without persistent infrastructure.

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Inspiration

We were inspired by the challenges of building real-time trading bots that are expensive, hard to maintain, and prone to infrastructure failures. Traditional bots require 24/7 servers, constant monitoring, and manual scaling. We wanted to reimagine trading automation by combining the power of AWS Lambda with scalping strategies and AI, creating a secure and fast solution that runs serverlessly, with almost no overhead.

What it does

BoltSniper AI is a high-frequency trading bot built with AWS Lambda as its core engine. It executes fast, secure trades by:

  • Receiving trading signals through API Gateway
  • Validating each signal using an AI module (with indicators like RSI, MACD, EMA)
  • Executing a BUY order only if the signal passes all safety checks
  • Dynamically assigning Take Profit (TP) and Stop Loss (SL) based on capital and context
  • Logging decisions for later analysis (optional future DynamoDB module)

The result is a smart, modular bot that can trade scalping strategies without a persistent server or manual intervention.

How we built it

We developed the bot in Python, using a modular design:

  • lambda_handler.py: Entry point, orchestrates all components inside AWS Lambda
  • strategy_engine.py: Technical analysis with RSI, MACD, Bollinger Bands
  • ai_validator.py: Signal filter, acts as an AI-based safeguard
  • order_executor.py: Executes orders (mocked for demo)
  • capital_guardian.py: Computes size and manages TP/SL logic

The entire system is deployed using the Serverless Framework, with API Gateway triggering the Lambda function on signal input. No infrastructure runs continuously — it's all event-driven.

Challenges we ran into

  • Deploying Python with TA libraries in a Lambda-compatible package
  • Keeping execution time low under Lambda’s constraints
  • Mocking Binance responses for demonstration without exposing real keys
  • Balancing AI logic with speed: rule-based logic was chosen over large models

Accomplishments that we're proud of

  • We created a fully modular, stateless trading engine that runs on-demand
  • Built a full scalping flow (signal → validation → order → TP/SL) under 200ms
  • Achieved our goal of creating a zero-infrastructure trading prototype
  • Engineered components that can scale into a full trading system in production

What we learned

  • Serverless architecture works for real-time trading if you simplify logic
  • Small, efficient AI logic can outperform large models when latency matters
  • The Serverless Framework is excellent for fast prototyping of finance tools
  • AWS Lambda + API Gateway = a powerful combination for automation

What's next for BoltSniper AI – Serverless Trading with Smart AI

  • Add DynamoDB for persistent trade logs and risk analytics
  • Extend to other exchanges (KuCoin, Bybit) via adapter modules
  • Enable SNS/EventBridge triggers for scheduled strategy checks
  • Add a frontend dashboard to visualize signals and performance
  • Package into a SaaS-ready solution for small traders and quant teams

Built With

  • ai
  • aws-api-gateway
  • aws-lambda
  • binance-api
  • chatgpt-(openai)
  • cloudwatch-logs
  • custom
  • numpy
  • pandas
  • python
  • serverless-framework
  • signal
  • ta-lib
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