Ophir Trading Platform
Fintech
All Case Studies

Rebuilding Ophir's trading platform for the speed and reliability their traders demanded

Ophir is a trading platform serving both retail and professional traders who need fast, reliable market execution. Live price feeds, high-frequency interactions, and absolutely no room for lag. When your users are making split-second decisions with real money, the tech has to hold up.

10x Faster execution speed
5x Faster deployments
3x Higher system capacity

The Problem

  • During peak trading hours, the existing system couldn't keep up with real-time price updates and the number of concurrent users hitting it at once.
  • Order execution had noticeable latency, enough to erode user trust and hurt actual trading outcomes.
  • The underlying architecture wasn't designed for growth. Every traffic spike caused slowdowns that rippled through the whole system.
  • Pushing new code to production was slow and risky. Deployments required downtime, which meant the team shipped less often than they needed to.
  • When things did go wrong, there wasn't enough observability in place to figure out what happened quickly.

“In trading, milliseconds matter. We needed a system that could handle live market data and execute orders instantly, without falling apart when things got busy.”

— Founder, Ophir

What We Built

We rearchitected Ophir's entire platform around real-time performance, horizontal scalability, and operational confidence, all while keeping active traders on the system.

  • A new event-driven architecture built from the ground up for live price feeds and instant order execution.
  • Backend services redesigned and optimized specifically for the demands of high-frequency trading operations.
  • WebSocket-based streaming for live market data with minimal latency, persistent connections, and smooth updates even under heavy load.
  • CI/CD pipelines that let the team ship updates frequently and safely, without taking the platform offline.
  • Proper monitoring, structured logging, and real-time alerting so the team spots issues before users do.
  • Reworked database queries and caching layers to keep response times tight even when traffic spikes.

Key Achievements

  • Rebuilt the trading platform around an event-driven architecture designed for real-time performance.
  • Brought execution latency down to milliseconds, right where it needs to be for live trading.
  • Scaled infrastructure to handle peak loads without degradation or manual intervention.
  • Gave the team the ability to ship updates frequently and safely through automated pipelines.
  • Added the observability layer the team needed to stay ahead of issues instead of reacting to them.

“Beitroot took a system that was holding us back and turned it into something we're genuinely proud of. It's fast, it's stable, and we're not afraid to push code anymore.”

— Founder, Ophir

Tech Stack

Node.js, well-suited for the kind of high-throughput, real-time workloads trading platforms demand. WebSockets for persistent connections and live data streaming with minimal overhead. AWS for scalable cloud infrastructure that flexes with traffic patterns. Redis for fast caching and data access on the read-heavy operations traders rely on. PostgreSQL as battle-tested relational storage for transactional data. CloudWatch paired with custom dashboards for full observability from infrastructure to application level.

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