Solutions and Differentiation 解決方案與差異化優勢

Deploy in days on any database with model-agnostic flexibility — without hardware lock-in or mid-market scale barriers.數天完成部署、任意資料庫與模型不綁定，擺脫硬體綼綁與中型市場規模門檻。

Competitive Specifications 競品規格比較

Phison AI Data Platform deploys in days on 10+ database types with model-agnostic flexibility and mid-market affordability.群聯 AI Data Platform 以數天部署、支援 10+ 種資料庫與模型不綁定，讓中型市場即可負擔。

Competitive Specifications 競品規格比較
Capability 能力 Hardware AI Platform 硬體 AI 平台 Traditional Data Platform 傳統資料平台 Phison AI Data Platform 群聯 AI Data Platform
Deployment Time 部署時長 Months 數月 6–18 months 6–18 個月 Days 數天
Database Requirements 資料庫要求 Any, no NL layer 任意，無 NL 層 Exclusive warehouse 專屬倉儲 Any, supports 10+ types 任意，支援 10+ 種
Model Flexibility 模型彈性 Requires GPU cluster 需 GPU 叢集 Vendor specified 廠商指定 Model agnostic 模型不綁定
Ecosystem Lock-in 生態綁定 Hardware bundling 硬體綼綁 Data migration required 需資料搬遷 Low 低
Min. Deployment Scale (USD) 最低部署規模 (USD) $500K–$10M+ $500K–$10M+ $500K–$1M+ $500K–$1M+ Affordable for mid-market 中型市場即可負擔

Investment Evaluation 投資評估比較

Shift from GPU-heavy OEM scaling to data-optimized economics with aiDAPTIV Cache Memory and built-in high availability.從高度依賴 GPU 的 OEM 擴充，轉向以資料優化與 aiDAPTIV Cache Memory 降低成本，並內建高可用架構。

Investment Evaluation 投資評估比較
Evaluation Aspect 評估面向 Traditional OEM Approach 傳統 OEM 作法 Phison AI Data Platform 群聯 AI Data Platform
Investment Model 投資模式 Heavily dependent on GPU/Server expansion 高度依賴 GPU/Server 擴充 Data-optimized first, lower GPU dependency 資料優化為主，降低 GPU 依賴
Operational Cost 營運成本 High GPU / Memory cost GPU / Memory 成本高 KV Cache lowers compute & build cost KV Cache 降低運算與建置成本
Performance Output 效能產出 Relies on hardware scaling 仰賴硬體 scaling Performance and cost optimized together 效能與成本同時優化
Risk Management 風險控管 Heavy multi-vendor integration 高度依賴多廠整合 Single platform integration 單一平台整合
Enterprise Capability 企業級能力 Requires extra HA architecture design 需額外設計高可用架構 Built-in HA / virtualization-native 內建高可用／虛擬化原生架構