| Complete data quality ecosystem in one platform | Data profiling, CleanAI™, MatchAI™, SmartMaster AI™, deduplication, entity resolution, audit logs, and automation. All modules in one licence. No extra add-ons or separate products. | Data quality platforms typically distribute capabilities across tiers ranging from $50,000 to $200,000+ annually before module or connector fees are applied. | Capabilities like matching, deduplication, entity resolution must be scoped, designed, and built as a separate component. A minimum viable data quality build typically requires $75,000–$250,000 before ongoing maintenance begins. |
| No coding, scripting, or developer resource required | A no-code, step-by-step workflow, including AI matching and entity resolution, without writing a single line of code. | Most enterprise SaaS platforms require connector configuration, API mapping, or scripting before data can be ingested and processed | Requires dedicated engineering resource across design, build, and test phases. |
| Time to first productive run | Most organisations complete their first full data quality run likely within 24 hours of installation. | Enterprise SaaS implementations typically run 6–8 weeks covering connector setup, API mapping, and configuration, before any data quality work begin | 6–12 months to reach a production-ready state. IT projects overrun their original timelines by an average of 50% and their budgets by 75% |
| Data processed inside your own environment | ✓ | ✕ | Achievable, but the full responsibility for designing, securing, and certifying the processing environment sits with your team. |
| AI matching, deduplication, and entity resolution | ✓ | ✕ | ✕ |
| Fixed, predictable cost with measurable ROI | ✓ | ✕ | ✕ |
