Back to Case Studies
NLPVector SearchProduction3 months
Semantic Deduplication at Ingestion
Hybrid retrieval and semantic scoring to remove duplicates before downstream pipelines.
Challenge
Syndicated feeds produced near-duplicates with minor edits, inflating storage and compute while missing subtle reprints.
Solution
Fingerprinting for fast filtering, ANN candidate recall on embeddings, and a semantic reranker with thresholds tuned for stability and low false merges.
Results
Cleaner upstream feeds for downstream NLP
Lower indexing load and less redundant processing
Stable dedup decisions across changing topics
Tech Stack
PythonSentence-TransformersApache KafkaMilvusRedisFastAPIKubernetes
Planning a production ML initiative?
Tell us what you want to automate or improve and we'll propose a clear, practical plan.
Request a Call