구형 시스템에도 AI를 탑재할 수 있나요?

네, ez2AI는 기존 시스템 수정 없이 AI를 탑재할 수 있습니다. API가 없는 레거시 시스템도 지원합니다.

데이터 보안은 안전한가요?

100% 안전합니다. 외부 인터넷 연결 없이 기업 내부에서만 작동하는 온프레미스 방식으로 정보 유출 위험이 없습니다.

개발 지식이 없어도 사용할 수 있나요?

네, 노코드 플랫폼으로 개발 지식 없이도 AI를 구축하고 운영할 수 있습니다.

어떤 문서를 지식화 할 수 있나요?

PDF, PPT, 워드, 엑셀, 이미지 파일 등 대부분의 문서 형식을 지원합니다. DB 데이터도 직접 학습/지식화가 가능합니다.

도입 기간은 얼마나 걸리나요?

기본 구축은 2-4주, 맞춤형 개발 포함 시 1-3개월이 소요됩니다. POC는 2주 내 가능합니다.

ez2AI Builder

AI that builds your company's systems

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One neural network model, three paths

Every ez2AI product shares the same neural network model at its core.

BasicAI that handles your company's work

BuilderAI that builds your company's systems

ModelA neural network model tailored to your company

Not code — design first

Vibe coding can never be the starting point

Vibe coding (code first)

ez2AI Builder (design first, with AI)

Skips design, jumps to code

Analyzes company knowledge, starts from design

Guesses without knowing structure

Neural network analyzes knowledge-ized data

Invents nonexistent info (hallucination)

Neural verification blocks hallucination (95%+)

Collapses at scale / legacy

Consistent via isolated child projects

Stops at the demo

Completed all the way to operation

① Knowledge-ization

The neural network model reads your documents, DB and workflows to grasp the structure.

② Design

Based on that knowledge, AI directly designs screens, DB and workflows.

③ Verify · develop

The neural network verifies design and code, completing it to company standards.

From your company's knowledge, not guesswork; from design, not code — ez2AI Builder.

A difference proven in numbers

What design-first AI delivers

Lower development cost

Knowledge-based design removes rework.

Faster development

A new menu produced in 20–40 minutes.

Development completeness

Neural verification and company standards, all the way to operation.

* Based on in-house projects vs. comparable SI. Varies by scale and scope.

Beyond RAG, ez2AI's Specialized Knowledge Conversion Technology

Unlike simple embedding RAG, ez2AI doesn't just vectorize data sources. It analyzes the structure, relationships, and context of each source to convert into knowledge that AI can truly understand.

Standard RAG

ez2AI

Processing Method

Text to vector conversion only

4 Core Technologies

Knowledge Level

Surface-level meaning capture

Structure, relationship, and semantic meta-knowledge conversion

Tech Stack

Single embedding model

4 knowledge conversion pipelines + composite stack

Data Source

Single type (mainly documents)

Documents, websites, databases

Output

Vector list

Structured knowledge base for LLM utilization

LLM Processing

Word-matching level

Accurate reasoning based on structure, meaning, and knowledge

Built-in domain-specialized neural network

Calls an external LLM separately

ez2AI-Core built-in

Unified structured + unstructured classification & connection

Structured only (auto graph)

Structured + unstructured in one neural network

Quantitative comparison vs global LLMs

(N/A)

+24.04%p lead under the test conditions

AI infrastructure & security you can adopt with confidence

Your data stays inside; only the minimum ever leaves

Where and on what it runs

Training · neural network model
DGX Spark — Runs on-site (hardware included)
Inference (answer generation)
OpenRouter — Freely choose Claude·GPT·Gemini — most cost-effective
Fully in-house inference (option)
RTX Pro 6000 — Air-gapped down to inference, zero external calls

The originals never leave your company

✓Document, drawing, photo and meeting originals are processed only on-site — zero external transfer
✓Only the user's question plus minimal context ever leaves
✓Option: air-gapped down to inference — fit for defense, finance, public and manufacturing

All that leaves is a single line of question. Your original data never leaves the company.

Key Features & Adoption Stages

See ez2AI's core features and adoption stages at a glance.

Level 1: AI Task Adoption

No workflow changes needed, auto-knowledge building while working

Level 2: Knowledge & Agent Setup

Based on accumulated work data, selectively supplement gaps with precision

Level 3: Full AI Transition

AI task automation with Builder for your own custom system

AI Tasks

Within 1 month

Start AI task management
Data collection
Auto knowledge building

Auto Knowledge

1-2 months

DB schema knowledge building
Key document screening
Specialized document knowledge

AI Agent

3-4 months

AI agent setup
AI task automation
AI reports & alerts

AI Builder

After 6 months

Custom AI Builder development
Internal AI capability building
Company-wide AI transition