Any Source. Any Format.
One Datalake.

EyesClear's data integration layer connects to your core banking, payment, and messaging systems — collecting, parsing, enriching, and storing every transaction in a unified datalake ready for real-time AML analysis.

Explore Data Integration →
7
Connector Types
5+
Message Formats
10K
Records per Cycle
On-Prem
Your Data Stays Inside

From Raw Data to Actionable Intelligence

A four-stage pipeline that collects transactions from any source, parses every field, enriches with business context, and stores it all in a structured datalake.

COLLECTConnectors pull data
→
PARSEMessageProcessor extracts fields
→
ENRICHScripts & lookups add context
→
STOREDataCarrier builds datalake
→
ANALYZEReady for detection

Connect to Any Data Source

Seven connector types cover every integration scenario — from real-time message queues to historical data migration and batch file processing.

⚡

JMS Connector

Consume messages from ActiveMQ and WebSphere MQ with SSL/TLS and HA clustering support.

Real-Time
♻

Kafka Connector

Stream data from Apache Kafka clusters with SASL/SSL security and consumer group management.

Real-Time
📁

File Collector

Monitor directories for SWIFT, JSON, CSV, and XML files with automatic parsing and error handling.

Batch
📄

SWIFT Processor

Parse SWIFT-FIN and ISO20022 XML messages directly from database tables into the analytics pipeline.

Batch
{ }

JSON Processor

Process structured JSON data from external database tables with multi-threaded batch operations.

Batch
🕒

Back-Dated Import

Migrate historical transactions from legacy systems with configurable time windows and batch sizing.

Migration
🔄

Rerun Engine

Reprocess existing messages by type, full scope, or custom SQL queries — ideal after rule updates.

On Demand

Intelligent Message Processing

The MessageProcessor converts every incoming message — SWIFT, XML, JSON, or CSV — into structured, enriched data through a configurable parsing engine.

🔍

Dynamic Field Extraction

Define parsing rules per message type using path-based expressions with fallback chains. Extract any field from nested JSON, XML, SWIFT tags, or delimited files.

  • Path-based expressions (/header/body/field)
  • Multiple fallback with & separator
  • String, numeric, date, and list field types
💻

Script-Based Enrichment

Attach JavaScript functions to any field for complex transformations, database lookups, and real-time API calls — all executed within a secure sandbox.

  • GraalVM JavaScript engine
  • Direct PostgreSQL query access
  • External REST API integration
🔗

Relational Linking

Automatically correlate related messages — amendments, confirmations, settlement chains — by establishing bidirectional relationships across FCT records.

  • Bidirectional message linking
  • Amendment chain tracking
  • Cross-reference validation
📊

Source Type Definitions

Group message types under Source Types that define format rules and transaction parsing logic for SWIFT, XML, and CSV input streams.

  • Regex & XPath transaction extraction
  • Multi-transaction message support
  • Template-driven field import

DataCarrier — Your ETL Powerhouse

The DataCarrier service automates data extraction from external databases, transforms flat relational data into nested document structures, and loads it into EyesClear's datalake with full incremental support.

🔌

Hierarchical Execution

Build parent-child dependency chains so that master data loads first, followed by dependent lookups and enrichment — all orchestrated automatically with collision avoidance.

🔁

JSON Merge Engine

Turn flat JOIN results into rich nested documents. Duplicate rows are consolidated by a merging field — accounts, addresses, and related entities become JSON arrays within a single record.

📈

Incremental Loading

Indexed fields enable efficient delta processing. The system tracks the maximum value per run and fetches only new or changed records — no full-table scans required.

CRM Tables & Full-Text Search

Mark any DataCarrier destination as a CRM table to enable full-text search directly from the EyesClear Search screen — making customer records, KYC data, and account information instantly queryable alongside transaction data.

PostgreSQL tsvector Indexing
Diacritic-Insensitive Search
Distinct Array Merge
Visual Data Carrier Designer

Formats, Channels & Databases

Out-of-the-box support for every standard in financial messaging and enterprise data infrastructure.

Category Supported Standards EyesClear
Message Formats SWIFT-FIN (MT103, MT202, MT700 …), ISO20022 (PACS, PAIN, CAMT), JSON, XML, CSV ✓
Message Queues Apache Kafka, ActiveMQ, IBM WebSphere MQ (with SSL/TLS) ✓
Databases Oracle, IBM DB2, Microsoft SQL Server, PostgreSQL ✓
File Ingestion SWIFT files, JSON files, CSV files, XML files — via directory monitoring ✓
Historical Import Back-dated message loader from any external database table ✓
Reprocessing Full, by message type, or selective SQL-based rerun ✓

Ready to Unify Your Transaction Data?

See how EyesClear connects to your systems, builds your datalake, and gets you detection-ready — fast.

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