Master data management software that governs product, asset, vendor, and customer records with AI-assisted validation and native SAP sync, so your AI and analytics initiatives run on data that's actually trustworthy.
300 to 800% Year-1 ROI, Payback in 4 to 6 months
Golden records in the
iContent Foundry
ISO-aligned taxonomy templates
SAP-certified integrations
Many AI initiatives stall or fail to deliver ROI simply because the underlying data is fundamentally flawed. Master data is scattered across disparate
ERP instances, legacy systems, and business-unit silos with conflicting naming conventions.
When master data lacks structure, forecasting models misfire on missing attributes, and analytics becomes compromised by inconsistent historical records. Data teams waste hours manually cleaning spreadsheets rather than focusing on strategic work.
Coding around bad data inside machine learning models increases technical debt and slows training speed. Manual scrubbing sprints provide only a temporary fix, as soon as new source systems roll in, data degrades back into disconnected silos.
PiLog DQG Suite combines AI, enterprise governance, and industry-specific business rules to forge trusted, standardized, AI-ready master data. It captures information from multiple sources, validates attributes, maps taxonomies, flags duplicates, and governs every record before it reaches SAP or your AI models
Standardize with industry taxonomies
Integration with the PiLog iContent Foundry applies internationally recognized classification standards (ISO, UNSPSC), giving AI models the consistency they need for accurate pattern recognition
Govern every record before it powers SAP and AI
Configurable, automated workflows, maker-checker hierarchies, role-based approvals, and mandatory attribute validation, ensure every record is validated before it goes live.
AI-powered deduplication
Fuzzy-match algorithms resolve duplicate and obsolete master records against ISO-aligned taxonomy, automatically.
Most enterprises start further left on this curve than they expect. PiLog DQG Suite is built to move you across it
Disconnected systems, legacy silos, duplicate records across ERP instances and source systems.
Attributes standardized against a shared taxonomy; duplicates
identified but not yet governed end to end.
Maker-checker workflows enforce validation before publication; Golden Records become the system of record.
Clean, governed, standardized data feeds forecasting, analytics, and AI models with consistent, trustworthy inputs.
What structured, AI-ready master data recovers once it's actually governed.
Inventory reduction, $3M to $10M+ in released working capital
Fewer emergency purchase orders and expedited-order costs
Year-1 ROI, with payback typically inside 4 to 6 months
| Criteria | PiLog DQG Suite | Generic MDM Tools |
|---|---|---|
| Pre-built content library | 50M+ golden records, 35K+ templates | Build it yourself |
| ISO standards adherence | ISO 8000, 55000, 27001, and more | Partial |
| SAP integration | SAP-endorsed app | Certified or not, varies |
| Implementation speed | 6 to 12 months | 12 to 24 months |
AI-ready data is clean, complete, standardized against recognized taxonomies, and governed by strict business rules, which lets ML models accurately understand relationships and patterns in the data instead of learning noise.
MDM software creates and maintains the single trusted "Golden Record" for an entity, material, asset, vendor, customer. Data governance layers policies, stewardship, and audit trails on top. DQG Suite does both in one platform rather than requiring you to stitch two tools together.
300+ SAP-certified integrations across S/4HANA (public and private), ECC, MDG, and Ariba, with real-time and batch synchronization, so governed records flow directly into the systems that consume them.
Yes. AI-assisted onboarding captures attributes from disparate source systems, then maps and standardizes them against ISO-aligned taxonomy before a record is governed.
Timelines vary with data volume and source-system complexity. Because taxonomies, validation rules, and SAP connectors are pre-built rather than developed from scratch, most teams move from fragmented to governed data in 6 to 12 months.
AI-assisted onboarding, validation, and enrichment across every master data domain.
Maker-checker workflows and audit-ready tracking on every record.
Golden Record governance combined with source-ready enrichment, in a single platform.
Get a personalized walkthrough of the PiLog DQG Suite against your real source data, with a quantified read on quality gaps today.
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