Enterprise AI
Enterprise AI Solutions
We build a tailored AI environment that understands your company's data and workflows and carries out real work.
YEJIN does not simply deploy a general-purpose AI service. We connect the documents, data, and business systems your company already owns to AI and build specialized AI Agents aligned with your organization's work procedures.
By combining AI Orchestration, RAG Knowledge Retrieval, data analysis and forecasting, Workflow Automation, and secure On-Premises technology, we deliver an integrated AI environment that supports how your company uses information and makes decisions.
- Internal enterprise data integration
- Tailored AI Agents
- RAG-based knowledge retrieval
- Business process automation
- Data analysis and forecasting
- On-Premises and sLM deployment
Challenges
AI is deployed, but it is not connected to real work
Companies hold vast amounts of documents and data, but that information is scattered across many systems, and repetitive tasks still rely on manual work. Even after adopting general-purpose generative AI, it cannot access internal information or understand your business rules and procedures, which limits its usefulness for real work.
Knowledge is scattered
Internal documents, manuals, business rules, and reports are spread across multiple repositories, so finding the information you need takes a lot of time.
Repetitive work is everywhere
Drafting documents, organizing materials, searching for information, writing reports, and entering data repeat constantly, making it hard to focus on core work.
It is not connected to internal data
General-purpose AI does not know your internal data or business systems, so it cannot provide answers or perform work aligned with your organization's standards.
Reliability is hard to judge
Generative AI answers may contain errors, omissions, and hallucinations, making them difficult to use directly for important work.
Data security is a concern
Entering internal materials and sales information into external AI services can lead to data leakage and loss of control over your data.
AI outcomes are hard to measure
Without clear target tasks, performance indicators, and an operating framework, AI adoption rarely translates into real productivity gains.
Our Approach
We connect your data, workflows, and security environment into a single AI architecture
Enterprise data integration
We connect documents, databases, ERP, CRM, groupware, and business systems so that your enterprise data can be used by AI in a structured way.
RAG Knowledge Retrieval
Drawing on internal rules, manuals, reports, and work materials, we retrieve information that matches the meaning and context of a question and reflect it in answers.
Tailored AI Agents
We build specialized agents suited to your departments, roles, and work procedures to perform information retrieval, document drafting, analysis, and repetitive tasks.
AI Orchestration
We select the right AI models, data, and tools for each objective and unify multiple processing steps into a single flow.
Data analysis and forecasting
We analyze enterprise data to identify key patterns and drivers of change and provide forecasts for demand, sales, inventory, and operational risk.
On-Premises and sLM deployment
For companies and institutions where security is critical, we build an On-Premises environment that runs on internal servers and air-gapped networks, along with a workflow-specialized sLM.
Solutions
Enterprise AI solution lineup
Enterprise Knowledge AI
Based on internal documents and data, it searches and organizes your organization's knowledge and provides answers together with supporting evidence.
Document Intelligence
It analyzes contracts, proposals, reports, policy materials, and other business documents to structure key content, risk factors, and comparison results.
Work-Support AI Agent
Aligned with role- and department-specific procedures, it performs information gathering, document drafting, reporting, review, and follow-up tasks step by step.
Customer Service AI
It classifies customer inquiries, retrieves relevant internal information, and generates draft answers aligned with your company's policies and standards.
Data Analysis and Forecasting AI
It integrates and analyzes structured and unstructured data to visualize the current state and forecast changes in demand, sales, inventory, and operational metrics.
Secure Private AI
For organizations that must limit transmission to external clouds, it builds an independent AI environment based on an internal network, dedicated servers, and a proprietary sLM.
Core Flow
How enterprise data is transformed into AI-powered work
- 1
CONNECT
Connect documents, databases, and business systems
- 2
UNDERSTAND
Understand meaning and context through RAG and vector search
- 3
ORCHESTRATE
Select the AI models, agents, and tools suited to the objective
- 4
EXECUTE
Perform retrieval, analysis, drafting, and repetitive tasks
- 5
VERIFY
Review the evidence, consistency, and accuracy of results
- 6
IMPROVE
Continuously improve based on user feedback and operational data
Scenarios
We design the scope of AI adoption to fit each department and industry
Corporate support
We improve the efficiency of corporate support work through internal rule search, report drafting, meeting-material preparation, and analysis of management information.
Sales and marketing
We analyze customer and market data and support the planning and drafting of proposals, marketing campaigns, and sales content.
Customer support
We automatically classify repetitive inquiries and generate draft answers grounded in internal policies and product information, improving service quality and response speed.
HR and training
We support internal-policy guidance, job-knowledge search, training-material creation, and employee-inquiry handling, strengthening how the organization transfers knowledge.
Manufacturing
We analyze production, equipment, and quality data to detect process anomalies and defect risks early, and support work-standard search, production planning, and equipment maintenance.
Distribution and retail
We analyze sales, inventory, ordering, and inbound/outbound data to forecast demand by product and support optimal inventory, order timing, and store and logistics operations.
Online business
We analyze visit, search, purchase, and churn data to understand customer behavior and support product recommendations, content personalization, ad-performance analysis, customer service, and order-management automation.
Agriculture and livestock
We analyze weather, growth, breeding, environmental-sensor, yield, and shipment data to detect disease and anomalies and support yield forecasting and decisions on feeding, irrigation, and shipping.
Procurement, logistics, and inventory
We integrate and analyze order information, suppliers, inbound/outbound flows, and inventory status to support purchasing plans, supply-chain management, inventory optimization, and logistics decisions.
Legal and compliance
We analyze contracts, statutes, and internal rules to structure key clauses, risk factors, obligations, and items requiring review.
Data analysis and decision-making
We integrate and analyze management, sales, and operational data to identify key metrics and drivers of change and support decisions based on forecasts of demand, revenue, cost, and risk.
R&D and technical support
We analyze technical documents, test data, patents, papers, and development history to support research search, technical comparison, report drafting, and development review.
Deployment
Deployment models
Cloud SaaS
A cloud-based AI environment for companies that need fast adoption and scaling.
Private Cloud
Run your enterprise data and AI services independently in a dedicated cloud.
On-Premises
A secure deployment model in which data and AI models are controlled directly on your internal network and servers.
Hybrid AI
A hybrid architecture that uses cloud AI and an internal sLM together according to the nature of each task.
Process
Adoption process
- 1
Work assessment
Analyze repetitive tasks, data structure, security policy, and AI adoption goals
- 2
Target selection
Select priority tasks and core KPIs that can be validated quickly
- 3
PoC design
Validate feasibility and performance using real enterprise data
- 4
System build
Build data integration, RAG, AI Agents, admin features, and a secure environment
- 5
Operation and enhancement
Analyze usage and performance metrics and continuously improve as work evolves
Impact
Changes you can expect, grounded in industry benchmarks
The figures below are not performance guarantees by YEJIN. They are industry reference indicators drawn from generative AI adoption research and case studies published by global AI companies and expert organizations.
Potential productivity gains in general office work such as document drafting and information organization
Potential productivity gains in customer service and consultation support
Potential improvement in processing speed for repetitive development and coding tasks
Potential daily time savings per employee on information search, drafting, and analysis
Share reporting improved work speed or output quality after using AI
Share of AI users who felt the effect of reduced working time
* Actual results may vary depending on data quality, target tasks, the scope of system integration, user proficiency, and the operating environment.
View references
- · McKinsey & Company: Productivity potential of generative AI in customer support
- · GitHub Research: Faster development-task completion when using GitHub Copilot
- · OpenAI Enterprise AI Report: Cases of reduced working time and improved output quality
- · Microsoft Work Trend research: Cases where AI users perceived time savings
Frequently Asked Questions
It suits companies whose internal documents and data are scattered across multiple systems, or that want to automate repetitive search, drafting, reporting, consultation, and analysis work. It can be applied across many industries, including manufacturing, distribution, online business, agriculture and livestock, architecture and construction, and professional services.
While general generative AI answers based on general knowledge, YEJIN's Enterprise AI solution connects your internal documents, ERP, CRM, groupware, and databases to provide answers and functions suited to real work. User permissions, audit logs, and security policies can be designed together.
Yes. Work manuals, contracts, reports, technical documents, and customer-consultation records can be connected via RAG and vector search, and ERP, CRM, groupware, electronic approval, document management systems, and databases can be integrated after we assess feasibility.
Internal knowledge search, report and proposal drafting, customer-inquiry classification, quotes and ordering, sales/inventory/demand analysis, production and quality data analysis, technical support, management-metric summarization, and repetitive data-collection, entry, and reporting tasks can be automated.
Yes. Before adoption we assess the types, formats, quality, duplication, and presence of personal information in your data. If data is insufficient or needs cleanup, we can first run a PoC on a single core task and then expand step by step.
It depends on the deployment model. It can be configured as a standard cloud setup, or, when security matters, with a Private Cloud, On-Premises, or sLM-based architecture that limits external transmission.
Yes. Using internal servers, dedicated GPUs, a local database, and an sLM, we can build a secure AI system suited to environments with restricted external internet access. Permission management, audit logs, and controls on data export are configured as well.
YEJIN's Enterprise AI solution can be designed on an AI Orchestration architecture. Depending on the objective, accuracy, cost, processing speed, and security requirements, you can choose or combine global LLMs, domestic models, open-source models, and an sLM.
Preliminary assessment and PoC typically take 4-8 weeks, a single-task build about 2-4 months, and a project integrated with business systems about 3-6 months. The exact timeline is set after reviewing requirements, data condition, integration scope, and security.
Yes. We provide ongoing support for model performance monitoring, RAG data updates, user permission management, security-policy review, incident response, server and GPU resource management, cost optimization, and feature expansion.
We design AI tailored to your company's data and work
AI transformation is not simply buying a solution; it is the process of connecting data, workflows, and the security environment into a single architecture. YEJIN supports the entire journey, from work assessment to PoC, tailored build, and operational enhancement.