Infoverity has spent more than a decade building governed, deduplicated master data for enterprises in distribution, healthcare, insurance, manufacturing and retail. The same data foundation now decides whether your AI use cases reach production or stall in pilots.
Customer records duplicated across systems. A product master that is half complete. Three teams using three definitions of “supplier.” Most enterprises have lived with this for years. The cost has been visible all along, now AI is making the cost impossible to ignore.
Why Infoverity. MDM is not a “Side Gig” for us. It is what we have built since 2011. More than 1,000 projects delivered. Over 200 enterprise clients. Programs running at 70M+ governed master records and more than a million API calls per day in production. That experience is also why our clients are asking us to design the AI strategies that sit on top of their programs.
Customer, product, supplier, location. Deduplicated, governed, kept clean over time. The kind of master data your analytics, your operations, and your AI models can all work from without anyone questioning the source.
Over 1,000 projects delivered. 200+ enterprise clients. Programs running at 70M+ governed records and a million API calls a day. We have seen most of what can go wrong in an MDM program and we know how to keep it from going wrong on yours.
Generative AI, agentic AI, and predictive models cannot reason reliably about entities that are duplicated, incomplete, or defined three different ways. Our MDM programs are designed with the AI use cases they need to support in mind.
We work across the major MDM and PIM platforms and recommend what fits your architecture, not what fits our margin. That independence is what makes the strategy credible and the implementation defensible to your Board of Directors.
Four patterns we see again and again. They start with the master data and end with what it makes possible.
A platform go-live is not the same as a working MDM program. Our Operational Excellence model sustains performance, handles enhancements, and applies AI to the operational work itself. One enterprise program runs at more than a million API calls per day at sub-300ms response times, including LLM-assisted merge request processing.
Most enterprises live with master data that is technically present and operationally unreliable. We diagnose where the discrepancies live, design the data model and stewardship process that fix the root cause, and stand up the matching, governance, and integration layers that keep the master record trusted over time.
Almost always, it is the data. Customer entities are duplicated, product attributes are missing, supplier records are inconsistent. We diagnose where the data foundation is breaking the AI use cases, then sequence MDM and AI as one program so the next pilot ships.
AI governance and data governance are converging fast. When AI outputs trace back to governed master data, accountability becomes possible, and so does the audit trail your regulators, board, and customers will increasingly ask for. We design both as one program.
Infoverity led three consecutive phases: enterprise data strategy, full implementation of Informatica Customer 360 MDM SaaS, and ongoing operational services. The result is a single authoritative customer record: deduplicated, address-validated, CCPA-compliant, and delivered reliably to every system that depends on it. LLM-assisted processing now handles stylist merge feedback at scale, putting AI to work on the operational data quality that keeps the platform accurate.
Build the deduplicated, governed customer master that powers reliable analytics, marketing personalization, and customer-facing AI. The foundation for recommendation engines, AI service agents, and accurate compliance response.
A single, enriched product record across channels and markets. Product data that supports omnichannel commerce today, and AI-powered search, generative product descriptions, and AI shopping agents tomorrow.
Master supplier, location, and reference data to support procurement analytics, supply chain risk modelling, and the AI use cases that depend on knowing who and where you are buying from.
Post-launch is where most data programs stall. Our Operational Excellence model sustains performance, handles enhancements, and applies AI to operational data work itself, so the foundation under your business keeps strengthening.
Governance is what keeps master data trustworthy after go-live. We design the operating model, roles, and policies that hold up under regulatory pressure and make AI outputs auditable when the question comes.
From use case prioritization through production deployment of generative, predictive, and agentic AI. The advantage: the master data the AI needs is already in our hands.
Ready to make your master data work as hard as your business needs?
Speak with an Infoverity advisor. In 30 minutes we will walk through where your master data sits today, the analytics and AI it needs to support, and the most direct path between the two.
No obligation — a 30-minute conversation to understand where you are and what your data and AI goals require.
