Case Study - Backend architecture for an AI-enabled translation platform
Systems-level backend development for Transleyt — an AI-supported translation, OCR, and media processing application requiring robust infrastructure and intelligent processing pipelines.
- Client
- Aicoor
- Year
- Service
- Backend Architecture & Product Infrastructure
Overview
Transleyt is an AI-enabled application developed by Aicoor that combines translation, optical character recognition (OCR), and media processing capabilities. The product requires a backend that can orchestrate complex processing workflows — handling document ingestion, text extraction, translation coordination, and result delivery — reliably and at scale.
Aicoor engaged yilven to design and build the backend architecture that powers the application: the API layer, data models, processing pipelines, and deployment infrastructure.
What we built
The backend was developed in Python with a PostgreSQL database, designed around a clear separation of concerns: API endpoints for client communication, processing services for OCR and translation workflows, and a data layer for managing documents, results, and user state.
Processing pipelines were designed to handle asynchronous, multi-step workflows — a document enters the system, passes through extraction and translation stages, and produces structured output. The architecture ensures that each stage is independently testable, recoverable on failure, and extensible as new processing capabilities are added.
The entire system was containerized with Docker, enabling consistent development environments, straightforward deployment, and horizontal scaling as the product's user base grows.
What we delivered
- Python backend
- PostgreSQL
- Docker
- Processing pipelines
- OCR integration
- API architecture
- Backend stack
- Python
- Data layer
- PostgreSQL
- Containerized
- Docker
- Processing pipelines
- Multi-step