RAGi - Enterprise AI Agent Platform

AI agents that search company knowledge, connect to internal systems and finish multi-step work

RAGi is an enterprise AI agent platform. RAG connects it to your internal knowledge base; AI agents then understand each request, break it into steps and call tools and internal systems, so work such as looking things up, organizing documents and writing reports runs on its own. It deploys on-premise or in the cloud; with on-premise deployment, model inference, documents and indexes can stay inside your environment. Used in finance, manufacturing, government and more.

RAGi is an enterprise retrieval-augmented generation (RAG) engine for knowledge management and question answering. A key feature is support for running large language models on-premise, so organizations can use AI while keeping sensitive data under their own management and reducing the risk of it leaving their environment.

RAGi supports multimodal content input including text, voice, images, and videos, as well as various common file formats and data sources. Enterprises can easily integrate scattered internal data to build a rich knowledge base. RAGi's built-in hybrid search engine combines keyword search and semantic understanding technologies, allowing users to quickly find the most accurate content, effectively reducing hallucinations and significantly enhancing the question-answering capabilities of large language models.

Multimodal Input

Supports various forms of data input including text, voice, images, and videos. Regardless of what type of documents your enterprise knowledge is stored in, RAGi can handle it with ease.

Hybrid Search Engine

Combines hybrid search technologies including keyword search and semantic understanding, capable of precisely understanding user intent, quickly retrieving the most relevant content.

Local Deployment

Can be deployed independently inside your own environment with no need to upload data to the cloud, so sensitive data stays under your control and the risk of leakage is reduced.

Unstructured Data

Possesses powerful unstructured data processing capabilities, able to quickly analyze and retrieve common file formats such as PDF, PPTX, XLSX, DOCX within the enterprise.

Knowledge Graph

Helps enterprises automatically construct knowledge graphs through intelligent retrieval, knowledge association, and other technologies. Enterprises can more intuitively understand their knowledge systems and discover hidden connections and insights.

Advanced LLM

Run Gemma 4, Muse Glimmer, the Nemotron 3.5 series and other models on-premise, or connect GPT, Claude and Gemini in the cloud, for multilingual understanding and generation.

AI Agent Capabilities

RAGi does more than answer questions. Its agents search the knowledge base, call tools and internal systems, and carry multi-step work from start to finish, with human review on the steps that matter.

Intent Routing

The system works out what the user wants and hands it to the right agent or knowledge base, so one entry point covers questions, policy lookups and tasks.

Task Planning

Agents break complex tasks into steps, retrieving data, calling tools and combining results in order, then deliver an answer or a report.

Integrations

REST API and MCP connect agents to your ERP, CRM, HR systems and intranet portals, so they work with the data you already have.

Visual Editor

Define agent roles, tools, state transitions and human-review steps in a visual editor, without coding from scratch.

Audit Trail

Every step records its sources, tool calls and results, for auditing, debugging and tuning workflows.

Access Control

Agents only reach the knowledge bases the user is allowed to see. LDAP and SSO are supported, and the whole stack can run inside your network.

AI Agents for OSINT and Social Listening

RAGi's AI Agents can read InfoMiner monitoring results and Social Media Data API collections over API, combine them with your internal knowledge base, and turn a stream of alerts into brief drafts analysts can work from. Conclusions are still verified by people before use.

From Alerts to Summaries

The Agent reads monitoring alerts, groups related news and social posts by topic, and keeps the source links that are available so analysts can check back.

Add Internal Context

It checks background material and past records in the internal knowledge base, lays out how an event developed, and lists what still needs to be confirmed.

Analyst Brief Drafts

Following the configured workflow, it drafts a brief and attaches the sources it drew on. Human review steps can be placed in the workflow so analysts check citations and conclusions before the brief is used.

RAGi - Enterprise AI Agent Platform

RAGi - Enterprise AI Agent Platformlogo

RAGi provides private enterprise AI solutions. It helps businesses break down data silos and integrate dispersed knowledge sources; enables intelligent Q&A and other innovative applications through local large language models; meanwhile, RAGi can seamlessly integrate with existing enterprise systems to achieve intelligent and automated business processes, greatly improving employee efficiency and work quality, accelerating digital transformation.

System Architecture

RAGi enterprise AI agent platform architecture

Product Interface

Homepage

Homepage

RAGi provides multiple core functions. Here, users can set up new conversations, browse various prompts to assist with operations, and view important system notifications. Additionally, users can easily add conversations and interact directly with RAGi, starting an intelligent dialogue experience.

Conversation Interface

Conversation Interface

When users ask questions, the system automatically searches for relevant information in the knowledge base. Meanwhile, it can identify user intent and connect to relevant Agents, expanding the conversation scope. Users can also filter data sources to enable the system to generate accurate and appropriate answers, meeting various query needs.

Configure Conversation

Configure Conversation

Users can select and connect different language models to adapt to various conversation needs. Meanwhile, they can set up relevant knowledge bases to ensure answers are based on the most relevant information. Additionally, through calling various tools and utilizing Agent technology, users can flexibly set up their own chatbots.

Multiple Data Upload Interfaces

Multiple Data Upload Interfaces

Supports various common data formats such as DOCX, PPTX, XLSX, or databases, making it convenient for users to upload and link various files. Users can also use the built-in web crawler to crawl specific links and web pages, greatly expanding the scope of knowledge sources.

Permission Settings

Permission Settings

Users can set various detailed permissions to ensure information security while promoting team collaboration. Notably, it allows other members within the same group to modify, read, and delete knowledge base content, achieving more efficient team knowledge management.

Knowledge Base Management

Knowledge Base Management

Users can comprehensively manage the knowledge base, including adding important knowledge content and deleting outdated or irrelevant information. Meanwhile, it also provides detailed permission management functions to ensure each user can access and manage the knowledge base within appropriate permission scope.

5

Multimodal Input (Text, Voice, Image, Video, Files)

2

Search Modes (Keyword + Semantic)

10

Supported File Formats

2

Deployment Modes (On-Premise + Cloud)

Industry Application Scenarios

Government Departments

Government Departments

RAGi's AI agents help civil servants find regulations, interpretations and past cases, and draft official documents in the required format. Incoming petitions and enquiries are classified, summarized and routed to a suggested unit automatically, with the case officer approving key steps.

Financial Industry

Financial Industry

AI agents answer customer and staff questions from internal policies and product documents, and compile client data into visit briefs. In compliance and risk workflows they screen names against lists and gather the records behind suspicious transactions for an analyst to decide.

Manufacturing Industry

Manufacturing Industry

AI agents search past design documents, patents and maintenance records to help R&D and shop-floor staff troubleshoot. When quality engineers raise an issue, the agent gathers defect records and the relevant specifications and lays out likely causes and fixes.

RAGi Solution Description

The private solution provides comprehensive localization solutions, including one-time buyout and continuous upgrade maintenance services, supporting multiple file formats and intelligent parsing functions, and can build local large language models. The cloud solution adopts a subscription model, utilizing the most advanced cloud language models (GPT, Claude, Gemini) and databases to provide customers with flexible and powerful AI dialogue and knowledge management systems.

  • Private Solution

    Buyout + Upgrade and Maintenance Fees

  • Supported Upload Formats

    docx, json, xml, html, md, pdf, pptx, xlsx, txt, csv, database

  • Intelligent Parser

    Parse PDF, PPTX, Excel, DOCX and documents

  • Intelligent Crawler Module

    Automatically extract target web pages and convert them to text files

  • Local Large Language Model Setup

    Deploy Gemma 4 (31B, 26B), Muse Glimmer, the Nemotron 3.5 series and other LLMs

  • Data Retrieval Module

    Vector retrieval, keyword retrieval

  • Vector Database Setup

    PostgreSQL + PgVector

  • REST API Module

    RAG Integration API, LLM API

  • Chatbot Conversational UI Interface

    Chat interface, file retrieval and selection, knowledge base creation and management, conversation management, permission settings

  • System Management Interface

    Permission settings, model control, LDAP and SSO settings

  • Cloud Solution

    Monthly Subscription

  • Supported Upload Formats

    docx, json, xml, html, md, pdf, pptx, xlsx, txt, csv, database

  • Intelligent Parser

    Parse PDF, PPTX, Excel, DOCX and documents

  • Intelligent Crawler Module

    Automatically extract target web pages and convert them to text files

  • Cloud Large Language Model

    Use large language models such as GPT-5.6 on Microsoft Cloud, or Claude, Gemini, and others

  • Data Retrieval Module

    Vector retrieval, keyword retrieval

  • Vector Database Setup

    Use Cloud Vector Database

  • REST API Module

    RAG Integration API, LLM API

  • Chatbot Conversational UI Interface

    Chat interface, file retrieval and selection, knowledge base creation and management, conversation management, permission settings

  • System Management Interface

    Permission settings, model control, LDAP and SSO settings

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FAQ

Last updated:

What is RAGi?

RAGi is LargitData's proprietary enterprise AI Retrieval-Augmented Generation (RAG) engine. It combines LLMs with your internal knowledge base, enabling employees to find internal documents, regulations, and technical literature through natural language conversations, with AI-generated precise answers and reports.

What can RAGi's AI agents do?

RAGi's agents first work out what the user needs, then search the knowledge base and call tools and internal systems (REST API, MCP) to complete multi-step work as a workflow: for example, compiling several documents into a report, answering staff questions according to internal policies, or pulling data from an ERP or CRM into a summary. Workflows are designed in a visual editor, key steps can require human review, and every step keeps an execution trace.

How is RAGi different from ChatGPT?

ChatGPT is a general-purpose AI assistant; its business plans can also take uploaded files and custom GPTs to add company data, and it is delivered mainly as a cloud service. RAGi is built for deployment inside the enterprise: it can run on-premise or in a private environment, retrieves from your knowledge base with RAG and cites sources for checking, controls access by department and role, and connects to internal systems to carry out multi-step work.

What file formats does RAGi support?

RAGi supports 10+ common formats including PDF, DOCX, PPTX, XLSX, CSV, JSON, XML, HTML, Markdown, and TXT. It can also crawl web content or connect directly to databases as knowledge sources.

Can I deploy my own language model on-premise?

Yes. RAGi's on-premise plan supports deploying large language models (such as Gemma 4 31B, Gemma 4 26B, Muse Glimmer and the Nemotron 3.5 series) within your internal network. All data and model inference runs entirely on-site with no external data transfer.

How does RAGi ensure data security?

RAGi offers on-premise deployment; when deployed on-premise, documents, indexes and model inference can all run inside your internal network. Built-in fine-grained permissions with LDAP and SSO integration limit each department and role to the knowledge bases they are authorized to access.

What languages does RAGi support?

RAGi uses multilingual LLMs, supporting Traditional Chinese, Simplified Chinese, English, Japanese, and other major languages for document parsing and Q&A. The system is specially optimized for Chinese document understanding and generation.

What size companies is RAGi suitable for?

RAGi suits SMBs to large organizations and government agencies. The cloud plan is ideal for SMBs seeking quick deployment; the on-premise plan suits finance, government, and manufacturing sectors with strict data security requirements. RAGi scales flexibly based on user count and knowledge base size.

Can RAGi integrate with existing systems?

Yes. RAGi provides REST API modules for integration with your existing ERP, CRM, HR systems, and internal portals. Through its Agentic RAG architecture, the system can automatically identify user intent and invoke corresponding tools and agents.

Further Reading