Regarding under the hood details, getting haystack up and running in the browser was quite a challenge, but here's what I ended up using: - Storage: IndexDB

Regarding under the hood details, getting haystack up and running in the browser was quite a challenge, but here's what I ended up using: - Storage: IndexDB browser API for local browser storage, it stores read permission tokens to apps, the AI models and the document index. - Indexing: fine-tuned TinyBERT-based bi-encoder for indexing documents, messages and emails. - Searching: cosine similarity between query embedding and the built index, and then rerank using tuned TinyBERT cross-encoder. - Building useful search resuts: search result building involved fine-tuning a t5-small model for summarization and text regression. - Performance nodejs->browser js adaptations, wasm rewrites in rust for performance.