* Note on engineering benchmarks: Latency measurements reflect internal benchmark testing environments under controlled loads with optimized B-Tree database indexes and API response caching. Actual production performance varies based on hardware provisioning, network conditions, payload size, and concurrent system load.
Challenge & Bottleneck
In Indian retail lending, every bank maintains distinct serviceability lists covering varying subsets of the country's pan-India postal PIN codes. Merging and querying these disparate lists in real time during customer onboarding was an operational hurdle.
Engineered Architecture Highlights
Normalized PostgreSQL relational database indexing Pan-India postal PIN codes.
Normalized PostgreSQL relational database indexing Pan-India postal PIN codes.
Composite B-Tree database indexes ensuring fast indexed query execution under heavy concurrent lookups.
Composite B-Tree database indexes ensuring fast indexed query execution under heavy concurrent lookups.
Fast, low-latency Fastify REST API endpoint serving live web frontend and mobile client applications.
Fast, low-latency Fastify REST API endpoint serving live web frontend and mobile client applications.
Batch CSV ingestion pipeline enabling non-technical operators to upload updated monthly bank policy sheets.
Batch CSV ingestion pipeline enabling non-technical operators to upload updated monthly bank policy sheets.
Key Engineering Decisions & Rationale
Composite B-Tree Indexes
Rationale: Standard full-table scans took ~450ms. Adding composite B-Tree indexes on `(pincode, bankId)` dropped query latency significantly.
Fastify Microservice Architecture
Rationale: Fastify's schema compilation delivered 3x higher throughput compared to standard Express servers for high-volume lookup traffic.
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