Case Study Web3 · AI trading bots

A thousand AI trading bots on one real-time engine.

This platform runs automated crypto strategies at scale. You configure a strategy, spin up many bots at once, and let them execute against live market data the moment it moves. We engineered the real-time core so the feed stays fast and the bots keep running, even when a thousand of them work the market together.

Client: Crypto Trading Platform
Sector: Web3 · Trading
Engagement: Engineering
Stage: Built · internal testing
Platform: Web app

The crypto trading platform with AI bots: a live market dashboard with price charts, running bots and real-time order execution — One engine: live market data, running bots, and order execution in real time.

By the numbers

−60%Latency, optimized WebSockets

1,000+Concurrent trading bots

99.9%Uptime

Real-timeExecution

Automated strategies break when the market moves faster than the system.

Running automated crypto strategies at scale puts two hard demands on one system: pull fast-moving market data without falling behind, and run many bots at the same time without breaking.

Crypto prices change by the second. A bot decides on the data it has, so a feed that lags by even a moment makes the bot act on a price that no longer exists. Stretch that across a thousand bots and the lag compounds.

Scale brings the second problem. One bot is simple. A thousand bots, each holding a live connection and reacting to the same market, will overwhelm a backend that was built for a handful. When one connection drops or one strategy throws, the system has to absorb it and keep the rest trading.

A real-time core tuned for scale, built to stay up.

We engineered the platform for real-time scale from the data feed inward. We tuned the WebSocket connections that carry live market updates and cut latency by 60%, so bots act on prices that are still true. The backend runs 1,000+ trading bots at once, and the error handling holds 99.9% uptime when a connection or a strategy fails.

What that meant in practice

Optimized WebSocket connections that cut market-data latency by 60%
A backend that runs 1,000+ concurrent trading bots without falling behind
Robust error handling that holds 99.9% uptime through dropped feeds and failed strategies
Real-time execution against live market data, with strategies you configure per bot

Dashboard

Live market data and every bot in one view.

The dashboard reads the optimized feed and shows prices as they move. You watch the market and the bots side by side, see which strategies are running, and check how each one is doing without leaving the page.

−60% latency · live market feed

Inside the product

Crypto Trading Platform — the AI trading bot configuration screen, where a user sets a strategy and parameters before launching a bot

Crypto Trading Platform — live trading and performance view showing bots executing orders against the market and their results over time

The hardest part

A thousand bots each want a live, low-latency view of the same market, and one failed connection cannot be allowed to take the rest down. We tuned the WebSocket layer to shave 60% off the feed latency, then built error handling around it that isolates a failure to the bot that hit it.

Ego Eimi Engineering note · the build

Built, in internal testing, and holding under load.

The platform is built and runs in internal testing. The numbers describe how the engine behaves under pressure, not how the market sits.

Under test it runs 1,000+ concurrent trading bots against live data, with the optimized feed holding 60% lower latency and the error handling keeping uptime at 99.9%. The next step is a wider rollout. For now the build carries the case: a real-time core that stays fast and stays up while a thousand bots trade on it at once.