Your documents.
Your machine.
Your answers.
A laptop-first AI assistant that finds answers across your files, cites its sources, and runs through a local LLM—without requiring a hosted AI API.
- Local inference
- Source citations
- Configurable expertise
The procedure defines four required actions:
- Record and contain the nonconformity.
- Complete a root-cause analysis.
- Define corrective action and an owner.
- Verify effectiveness before closure.
Document intelligence
without the cloud dependency.
Everything you need to turn local files into a searchable, conversational knowledge base.
Answers grounded in your files
Retrieval-augmented generation finds relevant passages before answering, with citations that point back to the source.
Local by design
Documents, embeddings, and chats stay on the configured host when Ollama runs locally.
Expertise you control
Create and save Agent Profiles that shape domain expertise, tone, and answer behavior.
Made for real documents
Index PDFs, Word documents, text, and Markdown—plus temporary attachments for a single chat.
Fast, streaming conversation
Read answers as they are generated and keep useful conversations in local SQLite history.
From document to cited answer.
A transparent local pipeline, designed to be inspected and extended.
Add documents
Choose files in the Knowledge Base or add an attachment to a chat.
Build the index
Text is split into searchable chunks and embedded into local ChromaDB.
Ask and verify
The local model answers from retrieved context and identifies supporting sources.
Keep sensitive context
inside your environment.
On-Prem RAG Assistant is built for a single trusted user running on a laptop or workstation. With a local Ollama endpoint, your content does not need to be sent to a hosted AI provider.
- ✓ Local model inference and embeddings
- ✓ Local document index and chat history
- ✓ Inspectable, MIT-licensed source code
Local execution is a privacy control, not a compliance certification. Operators remain responsible for access control, encryption, retention, and regulatory requirements.
Run it on your machine.
Python 3.10+, Ollama, and a few commands are all you need.
Read the full setup guide →scripts\setup.bat
macOS / Linux
chmod +x scripts/setup.sh && ./scripts/setup.sh
Installs dependencies and downloads the default local models.
Build private AI
on your own terms.
Explore the code, run it locally, and help shape the roadmap.