Private, offline RAG for iOS—powered by your documents and open‑source .gguf LLMs.
Last updated Apr 30, 2026
Key capabilities that make LocalRAG! stand out.
On‑device, offline Retrieval‑Augmented Generation (RAG)
Complete privacy with no data collection or sharing
Support for open‑source LLMs in .gguf format
Whisper‑powered on‑device speech‑to‑text transcription
Customizable system prompts for tailored behavior
User‑uploaded documents for grounded, low‑hallucination answers
Local indexing and retrieval for private knowledge bases
Runs entirely on iOS hardware—no server required
One‑time purchase with no subscriptions
Configurable model selection and parameters to balance speed and quality
Who benefits most from this tool.
Summarize readings and ask grounded questions using course materials, all offline.
Query papers and notes with citations drawn from a private, local corpus.
Draft emails and briefs with references pulled from internal documents on‑device.
Search interviews and transcripts locally and generate fact‑checked summaries.
Explore case notes and filings with retrieval‑backed answers that stay on device.
Consult local guidelines and protocols privately during offline workflows.
Answer FAQs from product docs without sending data to the cloud.
Query code snippets and docs locally to generate grounded explanations.
Use speech queries and offline RAG for itineraries and reference docs on the go.
Chat with a private assistant that never uploads personal data or conversations.
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