Demo Gallery
We don't just tell you.
We show you.
Demo videos of systems running in production, plus interactive demos you can try right in your browser.
Interactive
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Click a question above to watch how Qurify responds.
Retail & Commerce Full Demo
Weekend luxury sales analysis, partner settlement verification, VIP churn risk diagnosis, and return rate analysis — a full-screen demo of 4 scenarios with ontology ON/OFF comparison and knowledge graph visualization. All data is fictional.
Qurify Demo — Knowledge Graph Reasoning
One question, and the knowledge graph reasons its way to the answer
Watch the full process in real tax and accounting scenarios: the ontology maps ERP data, generates SQL, retrieves statutory grounds, and delivers a complete answer.
What is an ontology knowledge graph?
Qurify doesn't just search your data. It connects Evidence (source data), Concept (business concepts), and Neuron (reasoning paths) into a knowledge graph — precisely understanding the intent of each question and reasoning over causality.
- ①Map the natural language question to ontology nodes
- ②Auto-generate and execute SQL along knowledge graph paths
- ③Retrieve supporting documents from statutes and internal guidelines
- ④No path, no answer — hallucination blocked at the source
Evidence
Journals · ledgers · codes
Concept
Tax law · accounts · rules
Neuron
Reasoning paths · causality
Natural language question
→ ontology mapping → SQL → evidence → answer
Input VAT Deduction Ruling
0:48Ask whether the repair cost invoice for a company car is deductible — the ontology maps the question to tax law concepts and automatically presents the VAT Act §39 basis and the non-deduction reason code.
Real-Time Preliminary Closing & Cash Status
0:53Ask for today's preliminary closing in plain language — the system reasons across closing data, P&L, balance sheet, and cash position to deliver the real-time figures executives need.
Automatic Entertainment Expense Limit Calculation
0:49Ask whether cumulative entertainment expenses exceed the limit — the system fuses journal entries, statements, and corporate adjustment data to auto-calculate the statutory limit formula and warn of excess risk.
Account Classification & Journal Entry Recommendation
0:50Enter just a description — the ontology analyzes similar journal entry patterns to recommend the optimal account and entry, with evidence traceable through knowledge graph paths.
Demo structure — Each video runs 48–53 seconds in the order “As-Is → natural language question → ontology reasoning → knowledge graph answer → Before/After.” All figures use PoC scenario data.
Ontology ON vs OFF
With and without an ontology
For the same natural language question, compare how the presence of an ontology changes answer quality.
Q.Show me last quarter's top departments by revenue and their QoQ change
Without Ontology
SQL: SELECT dept, revenue → there is no single 'revenue' column; departments are code values (dept_code) and revenue requires aggregating transaction tables. Naive mapping fails.
With Ontology
Ontology: 'department' → dept_code → dept_name join / 'revenue' → SUM(transactions.amount) / 'QoQ' → quarter-over-quarter comparison logic. Returns accurate department rankings with change rates.
Q.How many recent contracts have auto-renewal clauses?
Without Ontology
SQL alone can't see the 'auto-renewal' clauses inside contract PDFs. Document content isn't in any DB column, so the query is impossible.
With Ontology
Hybrid RAG finds 'auto-renewal' clauses in the contract documents via semantic search and joins them with contract metadata in the DB. Returns the count with source passages.
Q.What share of this month's new sign-ups are active users?
Without Ontology
SQL: WHERE status = 'active' → the 'active' status value differs across systems, and the definition (logged in within N days) isn't specified, producing arbitrary results.
With Ontology
Ontology: 'new sign-ups' → created_at this month / 'active users' → last_login_at within the business-rule window. Standardized definitions return a consistent ratio.
Industry Scenarios
Question Scenarios by Industry
Example questions business users ask Qurify in each industry's real data environment.
ERP Tax & Accounting
“Is the repair cost for a company car eligible for input VAT deduction?”
The ontology checks vehicle type and usage data against tax regulations, returning a non-deductible ruling with the VAT Act §39 as its basis.
“Show me today's preliminary closing and cash position”
Even before month-end close, journal entries are aggregated in real time to return preliminary P&L and cash status within 30 seconds.
“How much have we exceeded this year's entertainment expense limit?”
Automatically computes the revenue-based limit under Corporate Tax Act §25 and reports the excess amount together with its tax impact.
Retail & Commerce
“Show me last weekend's luxury section sales versus the week before”
The ontology interprets the category and period conditions and returns the sales comparison instantly.
“Verify this month's partner settlement amounts”
Returns settlement verification results reflecting fee rates and promotion cost-sharing rules, with the full calculation basis.
“Which VIP customers are at high risk of churning?”
Combines purchase cycle changes with support history to flag at-risk customers and suggest actions.
Construction & Engineering
“What are the key checkpoints when supervising a NATM tunnel in soft ground?”
Combines accumulated supervision know-how with specification clauses to present a site-specific checklist.
“Analyze the main causes of schedule delay on this site”
Fuses progress and payment data with site reports to derive delay causes with supporting evidence.
“Walk me through the design change procedure and required documents”
Provides the exact procedure and step-by-step document requirements based on statutes and internal regulations.
Finance
“Give me a comprehensive risk diagnosis of this loan”
Combines borrower financials, covenant documents, and market data to lay out the risk factors with evidence.
“Show last month's top 10 branches by competitiveness metrics”
The ontology interprets the performance mart's complex aggregation logic, returning accurate rankings with the SQL as evidence.
“Which products are affected by this regulatory amendment?”
Semantically links regulation provisions to product terms, automatically deriving the scope of impact.
Public Sector — Production System
AI Civil Complaint Management System (live in Hongcheon County)
Role-by-role demo videos of Korea's first AI complaint system in full production, powered by a closed-network LLM.
AI Complaints — Admin: Today's Complaint Overview
An administrator monitors real-time complaint intake and keyword trends on the dashboard. This is a live feature of the Hongcheon County system, Korea's first AI complaint management system in full production.
AI Complaints — Assigner: AI-Powered Assignment
AI analyzes incoming complaints and recommends the best officer based on the org chart and duty assignments, completing assignment in one click.
AI Complaints — Handler: AI Answer Drafts
An officer reviews and refines the AI-generated answer draft to resolve a complaint, with statutes and similar cases presented as evidence.
Brand & Solution
Solution Introduction Videos
Qurify Solution Highlights
Highlights of the Qurify Agentic AI solution showcased at NextRise 2026.
Introducing SmartMind AI
Meet SmartMind AI — transforming how companies work with ontology-based Agentic AI.
Related pages
More demos — Industry demos for ERP tax & accounting, construction supervision, credit finance, and more are released progressively after customer approval. For a tailored demonstration, contact us and our sales team will arrange a private demo.