Source inventory and connection
We map where every piece of data lives (CRM, ERP, spreadsheets, in-house databases) and connect it to one shared place with reliable sync.
Service · Data Governance for AI
One source of truth for your people and agents
We connect and clean up the data in your CRM, ERP and spreadsheets: single definitions, quality checked daily, clear owners and role-based access. No committees, no slide decks.
DATA GOVERNANCE FOR AILIVE
What you get
Sourcesconnected inventory
Definitionsone per concept
Qualitydaily rules
Ownersone per domain
Accessby role and agent
The problem
Every team has its own version of the truth. And an AI agent reading contradictory data just makes mistakes faster.
Which?Nobody knows which number is right
Sales, finance and operations report different revenue or margin because each team calculates it its own way.
AgainThe same customer, many times
Duplicate and misspelled records make an agent quote, bill or greet the same company twice.
Who?Data with no owner
When a field is wrong nobody knows who should fix it, so the error comes back every week.
OpenUncontrolled access
Shared spreadsheets and exports give people and agents access to personal data they do not need.
What we build
Data governance that lives in operations, not in a committee. Rules that run on their own in your systems, with a named owner for every dataset.
Business data model
One definition of customer, order, margin or active account, agreed with each team and used the same way by reports and agents.
Monitored quality rules
Deduplication, normalization and validations that run every day and alert the owner when something breaks.
Owners and master data
A steward for each data domain and a master record of customers, products and suppliers that everyone uses.
Catalog and lineage
What data exists, what it means, where it comes from and which reports or agents use it, searchable by anyone.
Access, privacy and retention
Permissions by role and by agent, protected sensitive data and retention policies enforced in your systems, as defined by your team.
How we work
We start with the data your first AI use case needs.
- 01Readiness assessment
We assess sources, quality, definitions and access against the AI use cases you want to launch. You get a prioritized gap map.
- 02Design
We agree on definitions, owners, quality rules and access policies with each team. You get the data model and the plan.
- 03Build
We connect sources, merge records and set up rules and the catalog, with weekly reviews on your real data.
- 04Production
Rules run daily, owners get alerts, and reports and agents read from the same source of truth.
- 05Evolution
We add sources, domains and AI use cases on the same foundation and tune rules based on what operations show.
What you get
Data in order that stays in order.
- AI readiness assessment of your data
- Connected and documented source inventory
- Glossary with single business definitions
- Quality rules running daily with alerts
- Catalog with an owner and lineage per dataset
- Access and retention policies enforced in systems
Technology
Proven tools, configured for your business.
PostgreSQLCloud data warehouseCRM and ERP connectorsSpreadsheet syncETL and ELTData quality testsDeduplication and normalizationMaster data managementData catalogData lineageRole-based access controlSensitive data maskingAPIs and webhooks
Further reading
Related articles
Services
Data Governance for AI: How to Get Your Data in Order Without Endless Committees or Manuals Nobody Reads
Data governance for AI without the bureaucracy: single definitions, daily quality rules, owners and role-based access so people and agents share the same data.
Services
Is Your Data Ready for AI? The Checklist Before You Launch Your First Agent
Is your data AI-ready? A practical checklist covering sources, definitions, quality, owners and access to review before you put your first AI agent to work.
Strategy
Why Your AI Pilot Never Made It to Production (and How to Avoid It)
Why your AI pilot never reaches production: no harness, memory, evals, owner or approval flow. A practical checklist to close the gap without surprises.
Frequently asked questions
How is this different from a Company Brain?
A Company Brain organizes the knowledge agents read: documents, rules, manuals and cases turned into cited memory. Data Governance for AI organizes the structured data in your systems: definitions, quality, owners, lineage and access. They work together: the brain explains how your company works, and governed data gives it numbers you can trust.
Isn't this a never-ending project of committees and manuals?
No. We start with the data your first AI use cases need and deliver working rules, not a document. Committees are replaced by named owners and specific alerts.
Do we have to replace our CRM or ERP?
No. We work on your current systems, connect them and fix data at the source when it makes sense. If a system is truly holding operations back, we will tell you why and plan that separately.
Does this certify us for data protection?
We do not provide legal advice or certifications. We enforce in your systems the access, privacy and retention policies your legal or compliance team defines, and we keep a record of who accesses what.
Which data needs to be in order for your next agent? Tell us about your systems and we will propose a readiness assessment.
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