Assets Your Teams Reuse and Your Auditors Accept
Governed data products turn the datasets your teams keep rebuilding into named assets with an owner, a refresh schedule, and a record of where every value came from. We build them across your existing systems, so nothing moves off its source.
Explore our other solutionsThe Challenge
Data work rarely fails outright. It accumulates until nobody can say which version is current.
Everyone rebuilds the extract
The same customer or product dataset assembled repeatedly by different teams, each slightly different.
No owner, no refresh
Datasets that were correct the day they were built and have been drifting ever since.
Access decided case by case
Every request becomes a negotiation, so people copy data locally and governance loses sight of it.
Decisions nobody can reconstruct
No one can say what the numbers were when the call was made.
Each of these waits on someone who knows which system to trust. As decisions move to systems that act without a person in the loop, the question shifts from whether the data is available to whether it can be defended. A governed product answers both: someone owns and maintains it, so it's available when needed; and every value traces to a source, so it can be defended.
The Solution
Built across the systems you already run: one agreed record for each customer, product, and order, packaged into products someone owns, with governance and traceability underneath and decisions you can automate on top.
Trusted Records
One Record Wins, and It Stays Current
Matching records for the same customer, product, or order across systems. We define the rules with your team, apply them consistently, and keep the resolved record current as sources change. Rules get it wrong sometimes, so low-confidence matches route to a person for review, and nothing resolves silently.
Nothing moves off its system of record. The resolved view works across your platforms, so you get one answer without a migration, and every product, dashboard, and agent built afterward starts from that answer.
Entity resolution
Records describing the same thing merged into one, by rules your team agreed on.
Sources stay put
Resolution happens across your systems, with each source keeping what it owns.
Current by default
Sources change, resolved records follow, and nothing waits until morning.
Products & Ownership
Package It Once, So Nobody Rebuilds It
A data product is a dataset with a name, an owner, a documented contract, a refresh schedule, and someone who relies on it. We work with your teams to define which products are worth having, what each one promises, and how it's served: APIs, query interfaces, or MCP for agents.
Ownership is what makes it durable. A product with a named owner gets maintained when a source changes, so each one you build is one fewer thing the next project rebuilds.
Defined contracts
What the product contains, what it guarantees, and what consumers can rely on.
Named ownership
A person accountable for accuracy, freshness, and changes over time.
Reuse over rebuild
Each engagement leaves one more product behind, so the next use case starts further along.
Governance & Lineage
Know Where Every Number Came From, and Who Can Use It
Catalog, lineage, quality, and policy applied across your data and the live context AI draws on. Everything discoverable, every field traceable to its origin, and access enforced through the interface itself.
Agents get the same treatment as people: their own identity, their own permissions, and limits the system enforces, not just instructions given to the AI. When a decision needs reconstructing, the record of what was read and what was written is already there.
Catalog & discovery
People and systems find what exists without searching for someone who happens to know.
Field-level lineage
Every value traceable to where it came from and what transformed it.
Access controlled at the source
Access enforced where data is served, for people and agents alike.
Decision Intelligence
Agree Before You Automate
A decision is only as good as the agreement underneath it. If finance and marketing hold different definitions of revenue, a faster dashboard produces the disagreement sooner. Once the products underneath are governed, reporting moves from reconciling figures to deciding what to do about them.
Settled facts are what make a decision safe to hand to a system. Take a recurring call someone currently makes from three screens: once the inputs are governed, current, and reconstructable afterward, that call can move to a system, and the person making it goes back to the calls that need a person.
Consistent reporting
One definition behind every dashboard, so two reports stop disagreeing.
Automation-ready decisions
Recurring calls that can move to a system because the facts underneath them hold.
Improvement each cycle
Usage, quality, and outcomes measured, so products get sharper over time.
Pick the Dataset Everyone Keeps Rebuilding
Talk through which dataset your teams keep rebuilding and what a governed version of it would change downstream.
Outcomes
Done well, governed data products change how much the business can settle without routing it through a person.
Decisions that stop being debates
Two teams arrive with the same figure, from the same product, with the same owner behind it.
Requests that stay small
A data request resolves as a lookup, with no project queue in front of it.
Audit-ready by default
Lineage and access records already exist when someone asks how a decision was made.
Every agent on the same footing
Each agent you add reaches the same governed records, under the same limits, with the same trail behind it.
How Orium Helps
We resolve the records, package the products, and design the governance that holds them together.
Entity Resolution
Matching rules agreed with your team and applied consistently across sources.
- Match rule design and tuning per entity
- Resolution across ERP, OMS, PIM, CRM, and commerce
- Rules for which value wins when sources disagree
- Event-driven refresh so resolved records stay current
- Exception handling and manual review workflows
Product Definition
Identify which products are worth building, and write the contracts behind them.
- Consumer discovery and demand assessment
- Data product contracts, schemas, and guarantees
- Refresh schedules and freshness commitments
- Ownership model and accountability assignment
- Publication through APIs, MCP, and query interfaces
Governance Design
Catalog, lineage, policy, and access designed from the start.
- Catalog and discovery implementation
- Field-level lineage and attribution
- Policy and access enforced at the serving interface
- Per-agent identity, mandate, and authorization
- Audit records sufficient to reconstruct a decision
Operate & Evolve
Run the products with you as sources and definitions change, and hand them over when you're ready.
- Quality monitoring and drift detection
- Source change management and product versioning
- Usage and outcome measurement per product
- New product definition as use cases emerge
- Enablement so your team can run it without us
Build the Records Everything Else Runs On
Talk with our team about which of your data assets deserve an owner, clear rules, and a traceable history.
More Solutions
AI & Data Readiness
Learn moreFind out where your systems disagree and which of your AI plans the data can support today.
Search & Grounded Answers
Learn moreOne place for people, assistants, and agents to get answers, with sources cited and access controlled at the source.
Semantic Layer & Ontology
Learn moreOne agreed definition of products, customers, and orders that every system works from, with changes versioned so you can see what each one affects before it ships.
