Engineered a multi-modal RAG architecture handling 2M+ vector embeddings with sub-100ms retrieval latency and automated fallback routing.
<85ms
Retrieval Latency
1.2M+
Daily Vector Queries
99.99%
System Uptime
OpenAIPineconeLangChainPythonNext.js
01. The Problem
The client needed an enterprise-grade solution capable of handling high-volume queries with minimal latency, strict data privacy controls, and high availability during peak traffic spikes.
02. Engineering Solution
CookMyTech engineered a modular cloud architecture utilizing async background workers, vector search indexing, connection pooling, and automated fallback routing.
03. Key Technical Challenges
✔ Managing high-concurrency event bursts without memory leaks.
✔ Sub-100ms vector search querying over millions of document vectors.
✔ Implementing strict cryptographic logging and RBAC permissions.
✔ Automated CI/CD integration and zero-downtime rolling updates.
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