Document-based Conversational AI
AI learns hundreds of pages of manuals, regulations, and guidelines to instantly answer employee questions.
Auto-learn PDF, Word, Excel documents
Store document content in vector DB using RAG technology
Ensure reliability with source citations
Auto-link to original document pages referenced in answers
24/7 instant response
90% automation of HR and legal inquiries
Implementation Notes
Data governance required
Document version control, access rights, and security levels must be established beforehand.
Quality verification period
2-4 weeks for answer accuracy testing and improvement. Domain expert review required.
Estimated timeline
Use Cases
Unstructured Data Search from Reports and Sales Logs
Find documents based on meaning even without exact keyword matches, and provide summarized key content.
Semantic Search
Search for “customer complaint” and also find related terms like “claim” or “issue”
Automatic summarization
Extract key points from long documents in 3-5 lines
Integrate with existing systems
Easily connect with existing tools like SharePoint, Notion, and Confluence.
Implementation Notes
Quick implementation
Once documents are ready, a PoC can be completed within 1–2 weeks — one of the fastest ways to see real impact.
Search accuracy tuning
Improve accuracy by adjusting embedding models and chunk sizes. We recommend 2–3 iterative refinements.
Estimated timeline
Use Cases
Natural Language Database Queries
Ask 'What was the top-selling product in Seoul last month?' and AI automatically generates SQL to query the database and provide results.
Text-to-SQL auto generation
Convert natural language questions to SQL for DB queries
Auto chart generation
Visualize results as bar graphs, pie charts, etc.
Reduce Data Retrieval Time by 80%
Enable teams to analyze data on their own. No more IT requests.
Implementation Notes
DB schema information required
Table structure, column descriptions, relationship definitions must be documented.
SQL validation logic needed
Verify generated SQL is safe. Block dangerous queries like DELETE/DROP.
Estimated timeline
Use Cases
- • Sales dashboard (regional, product, time-based sales queries)
- • Inventory status (real-time stock levels, shortage alerts)
- • Customer analysis (purchase patterns, churn prediction)
More Application Areas
Apply AI across all business processes
Document Generation
Provide templates and data and let AI automatically generate complete documents.
Ready-to-use simple text generation
Auto-generate reports from Excel data
Additional time needed for DB integration and UI
Use Cases
• Weekly sales reports • Contract drafts • Technical documentation
Automated Data Extraction and Analysis
AI Agent automates repetitive data extraction, processing, and analysis tasks.
Auto-collect data from multiple DBs
Automate data cleansing and transformation
Additional development time for visualization requirements
Use Cases
• Monthly closing reports • KPI data collection • Anomaly detection
Technical Manuals and Equipment Documentation
Search and understand complex manuals with AI for faster access to technical knowledge.
Instantly find answers in manuals with thousands of pages
Query equipment specs and procedures in natural language
Multilingual search across technical documents
Use Cases
• Manufacturing equipment manual search • Medical equipment operation guides • Aircraft maintenance manuals
Fault Diagnosis & Troubleshooting
Leverage past incident logs and manuals to enable rapid issue diagnosis and resolution.
Symptom-based cause analysis and solutions
Auto-search similar past failure cases
Generate step-by-step troubleshooting guides
Use Cases
• IT infrastructure incident response • Manufacturing equipment diagnostics • Network problem solving