Overview

Incedo DataXel is Incedo’s next-generation data modernization platform built to help enterprises accelerate their cloud journey and unlock their full potential. It unifies data migration, transformation, and data quality under one intelligent framework — designed for scalability, accuracy, and trust.

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Incedo DataXel - Core Components

Incedo DataXel accelerates data modernization with its suite of GenAI-powered technical modules. These building blocks enable seamless migration from legacy systems to scalable cloud technologies, efficiently addressing specific enterprise use cases

LogicX

LogicX

Automates lineage mapping, dependency traceability, and process-flow visualization to decode legacy systems and establish a complete understanding of data logic before migration.

CodeX

CodeX

Transforms and optimizes applications from source to target platforms (Informatica PySpark, Teradata BigQuery, Oracle Snowflake, Shell Scripts DAG Airflows, etc.) using AI-driven conversion and syntax correction pipelines.

ReconX

ReconX

Performs automated data reconciliation, validation, and anomaly detection between source and target systems to ensure zero data loss and metric-level consistency.

OptimX

OptimX

Delivers performance optimization across queries and pipelines, leveraging AI-driven suggestions for indexing and partitioning.

DQxpert

DQxpert

Profiles datasets, detects anomalies, creates NLP-driven rules, and triggers automated remediation workflows to maintain trust throughout the modernization lifecycle.

Key Business Challenges

Unified Modernization Engine

An end-to-end platform that harmonizes logic extraction, code translation, code optimization, pipeline conversion, historical data migration and data reconciliation — streamlining data and application migration across heterogeneous systems.

Built-in Data Quality Assurance

Integrated DQxpert modules continuously profile, monitor, and remediate data quality issues — ensuring trustworthy analytics from day one of migration, while supporting multiple options for extracting data quality rules such as expert-driven, document-driven and AI-driven approaches.

Domain Contextualization

Ontologies and semantic models tailored for Banking, Telecom, Wealth Management and Life Sciences enable consistent logic alignment and data interpretation aligned with industry-specific nuances.

Enterprise-Grade Governance and Security

RBAC, audit logging, encryption and multi-cloud deployment guardrails ensure the platform meets the highest standards of compliance and operational resilience.

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A 5-step Data Modernization Framework

Discover & Assess

Inventory applications, databases and dependencies. Analyze code logic, objects and data dependencies to identify modernization candidates and target architectures.
01

Plan & Design the Migration

Define migration waves, success criteria and rollback plans. Map legacy code and ETL pipelines to target equivalents using pre-built accelerators and ontologies.
02

Execute & Transform

Translate code and data pipelines through CodeX and LogicX. Accelerate historical data migration through GenAI-based ETL and ELT script conversion.
03

Optimize & Validate

Run performance tests, enforce data integrity and optimize queries and infrastructure for speed, scalability and cost efficiency.
04

Operationalize & Govern

Deploy modernized, transformed data and code securely with end-to-end monitoring, policy governance and continuous improvement through AI-driven feedback loops.
05

Incedo DataXel - Powered Products

Unified Data and Code Modernization Suite

Brings together LogicX, CodeX, OptimX, HDI, and ReconX (powered by DQxpert) into a single platform that accelerates modernization while preserving business logic and data fidelity.

  • AI-driven end-to-end lineage, logic visualization, and code documentation
  • AI-driven code conversion and auto-optimization
  • Automated historical data ingestion/migration
  • Automated reconciliation and data health monitoring
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AI-Ready Data Quality Platform for Modern Data Teams

Brings together DQxpert’s capabilities for data profiling, rule automation, monitoring, remediation, and pipeline integration — all within a single, cohesive platform.

  • AI rule discovery from structured, unstructured, and document-based data sources
  • Automated anomaly detection and continuous data health monitoring
  • Seamless integration with pipelines and orchestration tools
  • Intelligent, context-aware remediation suggestions with AI and human review
  • Automated generation of audit-ready reports for compliance and traceability

Secure and Compliant Architecture

Built for trust, transparency and enterprise-scale resilience across modern data landscapes.
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Private VPC and hybrid deployment support

Private VPC and hybrid deployment support

payments

End-to-end encryption and RBAC

End-to-end encryption and RBAC

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Zero-trust network controls and audit trails

Zero-trust network controls and audit trails

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Model and pipeline governance for AI explainability

Model and pipeline governance for AI explainability

compliance

Multi-cloud flexibility — GCP, AWS, Azure, Snowflake, Databricks

Multi-cloud flexibility — GCP, AWS, Azure, Snowflake, Databricks

Business Impact

faster migration and code conversion timeline
Telecom 0 %
reduction in manual validation through reconciliation automation and DQ modernization
Financial Services 0 %
reduction in total cost of ownership through optimization
0 %

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