Dabarqus
Turn your data into LLM-ready memory banks with no-code RAG.
Quick facts
- Best for
- Turn your data into LLM-ready memory banks with no-code RAG.
- Pricing
- Freemium
- Editor rating
- 4.5 / 5
- Community saves
- 0
About Dabarqus
Dabarqus is a no-code Retrieval-Augmented Generation (RAG) app by Electric Pipelines that creates semantic memory banks from your documents, databases, emails, raw data, PDFs, and APIs, so large language models can access and use them as if in full context. With natural, LLM-style prompting, multiple portable indexes, and LLM-ready output compatible with ChatGPT, Ollama, and more, Dabarqus centralizes knowledge for accurate, context-aware responses. An admin dashboard offers real-time monitoring and testing, while a REST API, plus Python and JavaScript SDKs, enable developer control over ingestion, prompting, and built-in LLM inference—bridging no-code simplicity with robust, production-grade integrations.
Pros
- No-code RAG workflows for creating semantic memory banks
- Ingest documents, databases, and APIs (PDFs, emails, raw data)
- Natural, LLM-style prompting without custom query languages
- Multiple semantic indexes (memory banks) organized by subject or category
- LLM-ready output compatible with ChatGPT, Ollama, and other providers
- Admin dashboard with real-time graphs and built-in testing tools
- REST API for model downloads, prompting indexes, and LLM inference
- Native SDKs for Python and JavaScript
- Built-in chatbot and LLM inference directly via API/SDKs
- Context-aware retrieval across diverse data sources
- Portable memory banks for easy management and reuse
- Developer-friendly integration with standard tools