AIBPAL is your all-in-one archive database and local LLM archive which makes it easy to organize and access your private content without the risk of third-party access.
AIBPAL employs Retrieval-Augmented Generation (RAG) -- a technique that enhances Large Language Models (LLMs) by incorporating external content from a knowledge base before generating responses. AIBPAL converts your content into a RAG knowledge base.
AIBPAL uses its fully integrated database enterprise to organize and automatically converts your content into a private RAG knowledge base, accessible only by you.
AIBPAL™ SPECIFICATIONS
Schedule Your Demo TodayAIBPAL is a publishing platform and conversational research experience derived from your content. Take your knowledge base to a new level of discovery by uncovering isolated information not realized with typical archiving.
AIBPAL includes a built-in database enterprise, integrated LLM, with user access via chatbot query, search engine, or folder browse. This is a complete system designed as a plug-and-play network device. No internet connection, cloud services, or additional software required.
AIBPAL is built on our award-winning ArchiveInABox® database enterprise with full-featured user interface including mass uploader, indexer, and customizable indexes. Fully integrated OCR, search engine, LLM, and chatbot.
AIBPAL will process your private content for AI queries without exposure to outside networks. Bulk upload PDF, DOC, JPG, TIFF, PNG and more while simultaneously organizing in a standard folder tree. Comprehensive search index by file, folder, custom indexes, and OCR index, plus conversational chatbot queries.
AIBPAL maintains images of your original PDF, scanned documents, and photos which are displayed as thumbs and can be accessed for viewing at full size.
AIBPAL is work ready, with no complicated installation or setup. Works without internet connection. Intuitive browser-based user interface streamlines every aspect of user interaction. Just upload content and the system will automatically index for search, and process with LLM. No additional development is required.
©SmallTownPapers, Inc.
Private RAG knowledge base
AIBPAL employs Retrieval-Augmented Generation (RAG) -- a technique that enhances Large Language Models (LLMs) by incorporating external content from a knowledge base before generating responses. AIBPAL converts your content into a RAG knowledge base.
AIBPAL uses its fully integrated database enterprise to organize and automatically converts your content into a private RAG knowledge base, accessible only by you.
Benefits of a RAG knowledge base include:
Dynamic Updating -- RAG allows you to easily incorporate new information by updating the knowledge base it retrieves from -- each time you add content, it is automatically processed to be included in AI responses.
Relevant Responses -- RAG allows the built-in LLM to access your private knowledge base, making responses more accurate and relevant.
Real-Time Information -- RAG allows the built-in LLM to access current information, making responses more useful as your data changes and grows over time.
Combats Hallucinations -- RAG helps mitigate errors by grounding AI responses in verifiable data sourced from your knowledge base.
AIBPAL is uniquely compiled with open source and proprietary software and features Facebook Llama 3 LLM, Rockchip RK3588 SoC with 32 GB RAM, 8 cores utilizing the ARM RISC architecture, 2TB of storage, and an integrated GPU and NPU.
AIBPAL 32-8C-2TB RK3588 092025
