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LetzChat Translation Ecosystem

Building a real-time multilingual platform for global communication

LetzChat needed a production-grade platform that could handle translation across websites, calls, meetings, and documents with low latency and strong observability.

AI Translation and Communication2024 - PresentSenior Software Engineer / Backend Lead

Impact Metrics

300M+

Monthly Events Processed

100+ languages

Language Coverage

Web, Voice, Video, Docs

Channels Covered

Enterprise production

Deployment Scope

Tech Stack

Node.jsPythonWebSocketsSocket.IOOpenAI GPTWhisper AIAWSPostgreSQLRedisReact/Next.js

Problem

  • Global users needed real-time multilingual communication without workflow disruption.
  • Legacy translation tooling could not preserve context and speed at scale.
  • Infrastructure teams lacked unified visibility across high-concurrency translation workloads.

Solution

  • Built a modular translation ecosystem covering website translation, live calls, conferencing captions, and document workflows.
  • Implemented low-latency streaming pipelines for speech and text translation.
  • Added internal observability systems for server health, translation throughput, and operational diagnostics.

Architecture

  • Event-driven backend services with queue-based processing for workload isolation.
  • Hybrid AI model orchestration for translation quality and fallback resilience.
  • Admin analytics and monitoring dashboards for usage, quality, and infrastructure visibility.

Result

  • Scaled to 300M+ monthly events while maintaining reliable response times.
  • Enabled product expansion into Shopify, Square, Zoom, podcast, and voice-call integrations.
  • Improved debugging and incident response with real-time monitoring and operational metrics.

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