# SaiAkhil066/CORTEX-AI-SUPER-RAG

CORTEX RAG is an enterprise retrieval and knowledge assistant that helps teams find accurate answers from company data with citations, permission-aware retrieval, and fast deployment

Repository: https://github.com/SaiAkhil066/CORTEX-AI-SUPER-RAG
Canonical: https://ross.abutalabs.com/products/cortex-ai-super-rag
Language: Python
License: MIT
License Family: permissive
Last push: 2026-06-25T05:00:22+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 89, release rhythm 35, longevity 41
- inputs: {"age_days": 580, "days_push": 69, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1962, forks 291 (observed 2026-08-28T04:05:59.563732+00:00)

## What it is
CORTEX RAG is a local-first, agentic retrieval-augmented generation application that lets users upload PDFs and ask questions with cited answers, running entirely on their machine via Ollama. It combines nine RAG techniques including contextual retrieval, RAG-Fusion with reciprocal rank fusion, GraphRAG knowledge graphs, and corrective RAG chunk grading.

## Use cases
- ask questions about pdf documents with citations
- build a local rag chatbot without api keys
- chat with company documents privately offline
- retrieve answers from documents using knowledge graphs
- run a document question answering system with ollama
- improve rag recall with query fusion and reranking

## When to choose
- you need private, on-machine document Q&A with no cloud upload
- you want advanced RAG techniques like GraphRAG and CRAG in one pipeline
- you want cited answers from PDFs using local LLMs

## When to avoid
- you need a managed cloud RAG service with enterprise SSO
- you have no hardware to run local LLMs
- you need non-PDF enterprise connectors out of the box

## Facets
- artifact type: application
- maturity: active
- function: rag, search-engine, llm-inference, chatbot, pdf, nlp
- domain: large-language-models, artificial-intelligence, pdf
- platform: python, cross-platform, self-hosted
- tags: rag-fusion, graphrag, corrective-rag, ollama, streamlit, local-llm, knowledge-graph, citations, privacy-first, retrieval-augmented-generation, natural-language-processing

## Member repositories
- SaiAkhil066/CORTEX-AI-SUPER-RAG (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:59.563732+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:05:34.667456+00:00, confidence not recorded.
  - readme: https://github.com/SaiAkhil066/CORTEX-AI-SUPER-RAG (fetched 2026-08-28T04:05:59.563732+00:00, sha 803c6b38d3da)
- Data as of 2026-08-30T08:39:29.467469+00:00.