NeuRAG

An enterprise AI and knowledge management platform for building intelligent knowledge systems that combine organizational information with modern artificial intelligence.

Request a walkthrough →See it in healthcare

Product origin

NeuRAG is developed by Aurora Solutions, Inc. (USA), which has been building enterprise software since 1998. AI Industries is Aurora’s exclusive authorized implementation partner in the Philippines, responsible for local deployment, configuration, training and support.

The problem

Your best answers are already written down somewhere

Organizations store valuable knowledge across documents, reports, policies, procedures, spreadsheets, websites, and databases. NeuRAG lets people interact with that information in natural language, while keeping every response grounded in trusted organizational content.

Background

What is retrieval-augmented generation?

Traditional large language models generate responses based primarily on information learned during training. Retrieval-augmented generation, or RAG, adds a step: relevant information is retrieved from the organization’s own knowledge sources before a response is generated.

Answers can draw on

Organizational Documents
Policies & Procedures
Knowledge Bases
Reports
Databases
Websites
Internal Content Repositories

The result is more accurate, explainable, and context-aware responses that reflect the organization’s own information rather than relying solely on general AI knowledge.

Capabilities

What NeuRAG does

Enterprise Search
AI Assistants
Knowledge Management
Document Intelligence
Multi-Source Retrieval
Role-Based Security
Multi-Language Support
Integration with Commercial and Open-Source LLMs

Architecture

Flexible AI, chosen to fit your constraints

NeuRAG supports multiple deployment models, so organizations can balance cost, privacy, performance, and scalability on their own terms.

Commercial AI services: Use leading hosted models where capability matters most.
Open-source LLMs: Run open models where cost control and flexibility matter most.
Private AI deployments: Keep models and data inside your own environment where confidentiality requires it.
Hybrid architectures: Combine approaches so sensitive content stays private while other workloads use hosted services.

See NeuRAG on your own documents

Bring a folder of policies or manuals to the session. It is a far better test than any demo dataset.