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Connected intelligence
Compliance and analytics read the same data. Connecting their outputs reveals what neither could see alone.
When compliance, identity and analytics live in different products, each team sees a partial picture. A compliance analyst who finds a suspicious transaction has to consult another system to learn whether the user is verified. A dApp team that wants to understand the risk profile of its user segments simply cannot.
This fragmentation raises operating costs and lengthens the time it takes to detect threats. Ordellum Analytics runs all three services on one shared data backbone, so a risky wallet found by compliance appears in the relevant analytics segment at the same moment, and verified identity status can weigh into risk scoring.
Stage 1: Blockchain networks
Events are captured per network, so an issue on one chain never affects another.
Stage 2: Shared pipeline
Events are validated, decoded and corrected when a chain reorganises.
Stage 3: Three pillars
Compliance, identity and analytics consume the same verified events.
Stage 4: Evidence review
High-risk alerts are reviewed against regulation and precedent.
Stage 5: Human decision
An analyst decides with the full evidence bundle in front of them.
Each pillar publishes signals the other acts on. Select a direction to see which triggers flow which way.
Compliance
Wash trading detected
Analytics
Wallets are marked as artificial users
Priority: High
Compliance
Sanctions match
Analytics
Interacting wallets join a risk segment
Priority: Critical
Compliance
Mixer interaction
Analytics
Value is tracked as a separate TVL category
Priority: Medium
Compliance
Structuring detected
Analytics
Activity is removed from volume metrics
Priority: High
Analytics
Sudden activity spike
Compliance
A priority AML scan is triggered
Priority: High
Analytics
Cohort deviation
Compliance
A bulk risk assessment starts
Priority: Medium
Analytics
Bot-like behaviour
Compliance
Enhanced due diligence is triggered
Priority: High
Analytics
High-value user at churn risk
Compliance
A KYC renewal reminder is issued
Priority: Low
Showing 8 of 8 signals.
Filtering wash trading, bots, sybil accounts and sanctioned activity out of raw numbers yields Clean DAU and Clean Volume — metrics that reflect genuine usage. The effect can be striking: once bots are excluded, real retention is often higher than the raw figure suggests.
- Daily active users
- −18%
- 15,200 raw → 12,450 clean
- Trading volume
- −31%
- $18.5M raw → $12.8M clean
- Day-7 retention
- +20%
- 35% raw → 42% clean
Illustrative example from the platform specification.
The verification status that comes from the zero-knowledge identity module is used as a weighting factor in AML risk scoring. Profile risk — one of the five scoring dimensions — takes into account the user’s verification level, account age, previous alerts and whether a verified decentralised identifier is present.
Because the proof reveals only the verification result, compliance gains a stronger signal without the platform ever holding the user’s personal documents.