Project Scope
Client
Global Media Corp
Timeline
6 Months
Core Tech
Enterprise AI Content Engine
The Vision
Global Media Corp required a robust infrastructure to keep up with immense digital content demands. We engineered a massive LLM orchestration system leveraging GPT-4 and Claude to generate, proof, and translate thousands of daily articles dynamically without latency.
The Hurdle
Integrating large-scale models led to initial severe API rate limits and high latency during high-demand traffic spikes. Managing prompt contexts across 12 syntactically different languages resulted in hallucination errors.
The Architecture
Implemented an aggressive intelligent caching layer using Redis, combined with an asynchronous message queue. Fine-tuned the models using LoRA specifically strictly on the client's past 10 years of highly curated journalism.
Project Lifecycle
Phase 01 — Discovery
Extensive auditing mapping out core objectives, pinpointing bottlenecks in current architecture, and establishing pure technical strategy.
Phase 02 — UI/UX & Figma
We structured high-fidelity wireframes and interactive prototypes in Figma, prioritizing user accessibility and premium enterprise design languages.
Phase 03 — Engineering
Full-stack zero-latency development. We built the scalable microservices architecture incorporating parallel processing and WebSockets.
Business Impact
- Reduced content generation time by 85%.
- Achieved sub-500ms latency for translated outputs.
- Zero hallucinations reported during production.