See how Jev performs in a benchmark of 19 reranker configurations across five datasets, covering accuracy, latency, and prompt-driven relevance for LanceDB search.

LanceDB lets you tune search precision at query time, balance memory and disk caching, and keep new data searchable as your table grows.

Training a GPT-2-like model from raw text in 25 minutes with LanceDB, using one table for curation, tokenization, shuffling, packing, training, and analysis.

A deep dive into data loading for model training — the three pipeline stages, parallelism strategies, shuffling, caching, resumability, and how LanceDB's StreamingDataset fits in.

Run a multimodal feature-engineering pipeline in ten minutes with geneva-examples, then rebuild its CLIP embedding step with LanceDB's feature engineering API, the same calls you'd use to enrich your own tables on LanceDB Enterprise.

Volcano Engine rebuilt its AI data stack on Lance, cutting a seven-day pipeline to one day and powering agent memory with LanceDB at 100K+ QPS.

Learn how to build an OCR pipeline for handwritten medical notes using DSPy, GEPA, and LanceDB to manage images, labels, outputs, metrics, and retrieval.

How LanceDB's latest IVF_RQ improvements raise recall, cut p99 latency, and let teams tune vector search at query time with approx_mode.