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Enterprise Recommendation System
Scaling relevance and engagement for millions of end-users across enterprise SaaS deployments.
We rebuilt the candidate generation and ranking pipeline for a global SaaS platform. Our approach focused on achieving offline/online evaluation parity, addressing cold-start scenarios, and ensuring multi-tenant modeling constraints were respected at scale.
Measurable lift in downstream engagement in controlled A/B tests; production rollout with monitoring and reliable serving at scale.
Ranking
Retrieval
Offline/Online Eval
Multi-tenant
Production-Grade RAG
A knowledge-base RAG system that 'worked in demo' but hallucinated on real user queries and had no way to measure quality. We rebuilt the retrieval pipeline with hybrid search and reranking, introducing an evaluation harness with labeled queries and grounded-answer verification to ensure production-grade reliability.
Answer Quality Lift
Hallucination Rate Reduction
Reliable Serving at Scale
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