① AI Server Expansion Competition & Hardware Imbalance: The rapid expansion of the global AI server market is causing a surge in demand for GPUs and HBM3E. Consequently, with DRAM prices projected to rise by more than 40% year-on-year, companies trying to expand servers to secure AI leadership are facing immense cost-upward pressure.

② Operational Risk Due to DB End of Support (EOS): As support for major commercial databases ends, system upgrades are becoming essential. However, due to the explosive growth of data, existing SQL performance is hitting its limits, slowing down overall systems and leading to critical management risks where "performance degradation equals service interruption."

③ The 'Cost Trap' in Cloud Migration: Even when migration is pursued for cost savings, unoptimized SQL occupies excessive resources and causes budget overruns. According to IDC, approximately 10–30% of spending is wasted due to inefficient queries, which is a key cause of rising costs in pay-as-you-go billing models.

⓵ DBA Overload & Lack of Innovation (75% of work buried): Statistics show that over 75% of a DBA's working hours are buried in simple maintenance and repetitive troubleshooting. Especially as multi-DB environments accelerate, management difficulty has soared, but due to manual limitations, DBAs waste most of their time "fixing a single line of SQL" instead of strategic design or high-value tasks.

⓶ Decreased Developer Productivity (33% time loss): Developers also waste more than 33% of their working time responding to performance failures and fixing inefficient SQL. The difficulty of securing skilled tuners (45.5%) and the massive amount of time required for tuning (36.4%) are chronic causes that delay project deadlines and lower overall software quality.

⓷ 'Management Blind Spot' Buried in Top 5%: The amount of SQL a single expert can tune manually is around 50–100 cases per month. Consequently, companies only manage the "malicious queries" in the top 1–5% of the heaviest loads, leaving the remaining 95% of SQLs in a blind spot.

▷ Productivity Innovation: Through AI automation, more than 3,000 SQLs can be fully optimized per month, representing a productivity innovation of more than 50 times compared to human experts.

▷ 3-Step Intelligent Process

1. Extraction: Real-time capture of SQL showing signs of performance degradation, operating 24/7/365.

2. Tuning: SQL tuning or index recommendations powered by AI LLM, completed in just minutes.

3. Verification: Automated performance and data integrity comparison before and after tuning to ensure 100% reliability.

▷ Preventing Performance Degradation: Moving beyond reactive maintenance to an 'anticipatory management' system that preemptively blocks performance bottlenecks from the development stage.

⓵ Air-Gapped: Operates seamlessly in closed-network environments (on-premise) disconnected from the external internet.

⓶ Zero-Impact: The agentless architecture ensures no load on the DB server, allowing for safe operation without affecting active services.

⓷ Data Privacy: Collects only SQL information for performance analysis, strictly avoiding the collection of business data.

⓸ Short-Time: Delivers immediate tuning results from the very first day of installation, without the need for complex configurations.

▷ Operational Efficiency: By automating repetitive SQL tuning tasks 24/7/365, Query-Medic creates an environment where performance managers can focus on more strategic and value-oriented initiatives.

▷ DB Performance Stabilization: It preemptively detects and tunes underperforming SQL to prevent service disruptions and ensures high-quality SQL starting from the development stage, maximizing overall system stability.

▷ Enhanced Security and Reliability: It eliminates the risk of sensitive data leaks by reducing reliance on external tuning vendors. Furthermore, it prevents human error and enhances IT reliability by applying automatically verified, optimal tuning results.

▷ Cost Reduction: By optimizing DB resource utilization, it minimizes unnecessary hardware expansion and optimizes cloud usage costs, significantly lowering the Total Cost of Ownership (TCO).

▷ Improved Customer Satisfaction: It enhances the user experience by improving application response speeds and contributes to business competitiveness and customer retention through stable service delivery.

▷ Continuous Performance Improvement: Through AI learning capabilities, it consistently applies tuning patterns optimized for the client’s unique infrastructure. This creates a virtuous cycle where the quality of tuned SQL improves over time.