WebPizza AI - Private PDF Chat
POC: Private PDF AI using only your browser with WebGPU
# Documents AssistantWhat is WebPizza AI - Private PDF Chat?
I built this POC to test if complete RAG pipelines could run entirely client-side using WebGPU. Key difference: zero server dependency. PDF parsing, embeddings, vector search, and LLM inference all happen in your browser. Select a model (Llama, Phi-3, Mistral), upload a PDF, ask questions. Documents stay local in IndexedDB. Works offline once models are cached. Integrated WeInfer optimization achieving ~3.76x speedup over standard WebLLM through buffer reuse and async pipeline processing.
Problem
Users need to process PDFs for AI-driven insights but rely on server-dependent solutions, exposing privacy-sensitive documents to third-party risks and requiring reliance on server infrastructure and internet connectivity.
Solution
A browser-based AI tool where users can run client-side RAG pipelines without server dependency, uploading PDFs, selecting local AI models (e.g., Llama, Mistral), and querying documents offline with all data stored in IndexedDB.
Customers
Researchers, legal professionals, and developers handling confidential documents (e.g., medical records, legal contracts, proprietary code) requiring strict data privacy.
Unique Features
Entirely client-side processing via WebGPU for embeddings, vector search, and LLM inference; offline capabilities; integrated WeInfer optimizations (3.76x faster than WebLLM); local model caching.
User Comments
Ensures complete privacy with zero data leakage
Works seamlessly offline after initial setup
Faster processing with WebGPU acceleration
Flexibility to choose different AI models locally
No backend setup or costs
Traction
Early-stage POC with WebGPU integration; WeInfer optimization achieving ~3.76x speedup; supports Llama-3-8B, Phi-3, and Mistral models; no disclosed revenue or user count yet.
Market Size
The global AI-based document processing market is projected to reach $7.9 billion by 2028 (Source: MarketsandMarkets, 2023).
