Master data management · use case

MDM with Knobs

Traditional MDM reconciles records. EKIP optimizes them treating every attribute as a measurable signal and surfacing exactly where uncertainty lives.

Selection Knobs Creation Knobs Control Knobs Information Geometry Golden Record Intelligence
Traditional MDM asks
"Which record is correct?"
Rules pick a winner. Last-write wins, or source-system priority decides. You get a reconciled record but no signal about how confident to be in any of its attributes.
vs
EKIP asks
"Which attributes carry the most signal about this entity's true state?"
Knobs score every attribute by information density across sources. The golden record isn't just reconciled it's the highest-information-density representation of the entity, with confidence scores attached.
The gap

Same entity. Fundamentally
different treatment.

Both approaches start with three conflicting source records. What they do next is where every downstream AI accuracy problem originates.

Traditional MDM vs EKIP Knobs comparison ── vs ── Traditional MDM Salesforce Acme Corp (v1) SAP ACME CORP (v2) Billing Acme Corporation Rules engine last-write-wins Golden record Acme Corp · no confidence What you get: A frozen artifact No attribute signal No confidence score Rules disagreed silently Ambiguous entities surface no warning EKIP Knobs Salesforce density 0.91 ↑ SAP density 0.43 Billing density 0.28 ↓ Selection knob scores by signal density Golden record Acme Corp · confidence 0.87 What you get: Confidence score Attribute signal map Living record Resolution queue Ambiguous entities surfaced and ranked
How EKIP acts on master data

Three knob types.
One coherent MDM strategy.

Every MDM problem survivorship, enrichment, governance maps cleanly to a knob type. No new abstractions. Same EKIP platform.

Selection Knobs

Survivorship intelligence

Score each source-system value by information density, not just recency or system priority. The surviving attribute is the one with the highest outcome-relevant signal.

  • Source reliability scoring per attribute type
  • Match confidence thresholds for entity resolution
  • Field-level density ranking across all sources
  • Conflict detection with resolution suggestions
Creation Knobs

Entity enrichment

Identify entities with sparse attribute coverage and generate targeted enrichment strategies. Build the datasets that fill the gaps without adding noise.

  • Attribute coverage scoring per entity segment
  • Cross-system identity stitching (unified customer ID)
  • Synthetic enrichment for sparse attribute clusters
  • Information density gain tracking post-enrichment
Control Knobs

Governance as policy

PII classification, retention rules, stewardship assignment, and regulatory exposure all expressed as auditable, controllable knobs rather than one-off manual tagging.

  • PII tagging at attribute level (GDPR, CCPA, HIPAA)
  • Retention and purge policy enforcement
  • Stewardship assignment and escalation rules
  • Regulatory flag propagation across entity types
Information geometry for MDM

Know exactly where to act
in your entity population.

EKIP maps every entity across two dimensions attribute completeness and source certainty revealing the frontier zones where knob action has the highest leverage. Click any entity to see its attribute profile.

Interactive entity information geometry Scatter plot of banking entities across certainty vs completeness axes. Click any dot to see its attribute profile. sparse + uncertain deprioritize complete + certain · golden record zone complete · uncertain → enrichment target sparse · certain → coverage target attribute completeness → source certainty → 0 0.5 1.0 0 0.5 1.0

click any entity to see its attribute profile · click background to close

Selection knob in action

Attribute-level survivorship
for a banking customer.

Each attribute is scored independently across CRM, Core Banking, and KYC/AML. The source that wins isn't always the same it's whichever carries the most information density for that specific field.

Banking customer survivorship knob CRM Core banking KYC / AML Selection knob → survivor Legal name Address Risk rating ID / PAN Rel. manager Priya Sharma density 0.62 Priya K. Sharma density 0.91 ✓ P. K. Sharma density 0.48 Priya K. Sharma core banking (0.91) 12 MG Road, Pune density 0.87 ✓ 12 M.G. Rd, Pune density 0.71 Pune, MH density 0.33 12 MG Road, Pune CRM (0.87) Medium density 0.40 density 0.05 Low-Medium density 0.88 ✓ Low-Medium KYC/AML (0.88) BKRPS1234K density 0.31 BKRPS****K density 0.18 density 0.06 ⚠ conflicted Control knob: PII lock Anil Mehta density 0.83 ✓ A. Mehta density 0.55 density 0.09 Anil Mehta CRM (0.83) highest density → attribute survives all sources low / conflicted → Control knob flags PII, blocks auto-merge
Golden record, redefined

Not a frozen artifact.
A living intelligence profile.

An EKIP golden record is the highest-information-density representation of an entity at a point in time with a confidence score, an attribute signal map, and a prioritized resolution queue built in.

Traditional golden record
Legal name
Address
Risk rating
ID / PAN
Rel. manager
no confidence signal
no resolution queue
EKIP golden record · Priya K. Sharma
Legal name
0.91
Address
0.87
Risk rating
0.88
ID / PAN
0.31
Rel. manager
0.83
overall confidence 0.76
ID / PAN conflicted · stewardship review required
KYC refresh overdue by 14 days
Closed-loop knob lifecycle

MDM is not a project.
It's a continuous loop.

EKIP's six-stage lifecycle maps directly to MDM from surfacing high-conflict entities to governing the golden record as a live, auditable artifact.

MDM knob lifecycle six stage closed loop MDM knob lifecycle 1 · Discover find high-conflict entities by information gap score 2 · Define specify outcome-relevant attributes per entity type 3 · Instrument connect CRM, core banking, KYC, Snowflake 4 · Prioritize rank entities by information gap in frontier zones 5 · Optimize apply survivorship knobs; enrich sparse entities 6 · Govern PII, retention, stewardship as Control Knobs Discover / Define / Govern Instrument / Prioritize / Optimize
AI context layer

AI agents don't just need a golden record. They need to know how much to trust each attribute.

The metadata management view describes an "AI Context Layer" as the newest capability. EKIP delivers that layer not as catalog metadata, but as knob intelligence. Every attribute carries its density score, its source lineage, its confidence signal. When an AI agent asks about a customer, it gets the value and the epistemic context behind it.

"What is Priya Sharma's risk rating?"
valueLow-Medium
sourceKYC/AML system
density0.88 high confidence
freshness14 days since last refresh
conflictsCRM shows Medium (0.40)
actionKYC refresh recommended

Start treating master data
as infrastructure.

EKIP brings knob intelligence to your entity population so golden records are optimized, not just reconciled.

Explore EKIP → See the platform