CorpusKit Studio

Build semantic search corpora from your documents.

Turn any PDF or EPUB into a deployable RAG corpus package — no terminal, no Python, no manual file management. Embeddings are generated entirely on-device. Built for developers and content curators building knowledge-first apps.

Universal app — one purchase for iPhone, iPad & Mac

PDF & EPUB import

Drag in any PDF or EPUB. CorpusKit Studio extracts text using Apple's native frameworks — no third-party tools or Python required.

Smart text chunking

Configurable chunk size and overlap in pure Swift. Preview your chunks before embedding to dial in the right settings for your content.

On-device embeddings

The embedding model runs via Core ML on your device's Neural Engine — fast, private, and shared across the CorpusKit ecosystem.

Live retrieval testing

Query your corpus in real time before you ship. See ranked results with cosine similarity scores to validate your chunking strategy.

Highlight & rate

Read your source document inside the app. Highlight passages and rate their importance — curator signals travel with the exported corpus.

Signed .corpus export

Export a signed bundle consumable by any CorpusKit iOS app. Includes chunks, embeddings, metadata, and your curation data.

CorpusKit Studio onboarding, introducing the corpus building workflow
Start a new corpus
Chunk inspector showing extracted passages and their settings
Inspect every chunk
Export screen preparing a signed .corpus bundle
Export a signed bundle

Developers building RAG apps

Stop wrangling Python pipelines to create embeddings. CorpusKit Studio is a native app that produces corpus bundles your iOS app can consume directly — no backend required.

Researchers & knowledge workers

Highlight the passages that matter, rate their importance, and export a corpus that reflects your expertise — not just raw text extraction.

Private document collections

Process sensitive documents entirely on-device. No data leaves your device during embedding. Distribute corpora to your team without a cloud intermediary.

All local

Every document, chunk, and embedding stays in the app's own storage — visible via Finder on Mac or the Files app on iPhone and iPad. Nothing is sent to external servers.

On-device ML

Embeddings run via Core ML on your Neural Engine. No API calls, no cloud inference, no data leaves your device.

No account required

Download and use immediately. No sign-up, no email, no subscription. Sensitive settings stored in Keychain.

App Sandbox

The app operates within Apple's security sandbox. File access is managed by the system — only files you explicitly open are accessible.

No Python, no heavy dependencies. Native performance throughout.

Document importPDFKit (PDF) · EPUB parser
EmbeddingsCore ML · on-device model
Vector searchAccelerate vDSP
PersistenceSwiftData
Export signingCryptoKit
PlatformiOS 26+ · macOS 15.6+

Requirements

  • iPhone, iPad, or Mac
  • iOS 26 or later · macOS 15.6 or later
  • Available on the App Store
  • No internet connection required

Privacy

CorpusKit Studio collects no personal data, has no accounts, and makes no network requests during normal use. Read the full privacy policy.