Human validation precedes approved reuse.
MS6 ENTERPRISE GENOME
Know what connects.
See what changes.
A product vision for recovering enterprise knowledge and making systems, data, business rules and dependencies understandable.
ASK YOUR ENTERPRISE
“If we change this system,
what else changes?”
INTERACTIVE PRODUCT CONCEPT
From unknown dependencies
to an informed decision.
Explore an illustrative enterprise. Choose a perspective to see what the product helps you understand.
ILLUSTRATIVE ENTERPRISE MAP
Enterprise
Genome
Genome
Select an asset to see its relationships.
THREE DIFFERENT ROLES
Meaning. Knowledge. Simulation.
A shared language
Defines the entities, relationships and rules used to describe the enterprise consistently.
Example: a process uses an application, and an application reads data.The enterprise knowledge
MS6's product concept combines recovered knowledge, relationships, evidence, confidence and human validation.
Example: which process uses this system, who owns it, and what evidence supports that relationship?A model for change
A representation linked to enterprise state and dependencies, used for scoped analysis and scenario exploration.
Example: what might change if this application moves to a new environment?Genome is the MS6 product concept. An ontology is a modeling foundation. A digital twin requires maintained state, validated assumptions and an appropriate simulation model.
ENTERPRISE TRUTH GRAPH / A LAYER WITHIN GENOME
Every finding has evidence.
Every conflict needs review.
Connect the knowledge you recover with source versions, unresolved questions and accountable human review.
How do you know this is true?
Link each discovered rule or relationship to its supporting policy, code, document or process record. Compare the sources, retain their versions and surface disagreements.
For example, a policy requires an approval but the implementation has no matching check. The finding stays marked for review until an accountable owner examines the evidence and records a decision.
A review records who checked the finding, when and within what scope. A numeric confidence score alone does not establish correctness.
Illustrative concept. No real customer records.AI TRANSFORMATION ARCHITECT
Understanding becomes a plan.
Data migration
Mappings, cleansing priorities and reconciliation checks.
Application modernization
Dependencies, business logic and integration boundaries.
Infrastructure modernization
Workload context, access requirements and recovery planning.