DataReconRemit is an AI-Driven, cloud-agnostic framework designed to streamline and automate data reconciliation and validation during data migration phases—ensuring accuracy, integrity, and audit-readiness of both historical and incremental data loads.
Data reconciliation ensures that the data migrated to the cloud matches the source data in terms of volume, structure, and accuracy. Data remit process focuses on identifying, reporting, and addressing discrepancies post-migration.
Ensure seamless integration of historical data with incremental loads, enabling real-time or near-real-time updates without data conflicts or quality issues. Organizations can achieve a successful and reliable migration while minimizing risks and optimizing performance.
Main Characteristics of DataReconRemit:
Automated Reconciliation
Automates validation of historical and incremental data across on-premise and cloud
systems.
Cloud-Native & Cross-Platform Compatible
Supports BigQuery, Redshift, Snowflake, Azure Synapse, and common data formats like CSV, JSON, Parquet.
Granular Integrity Validation
Performs row-level, column-level, and aggregate comparisons with checksum and hash audits.
Schema Drift Handling
Detects mismatches in data types, lengths, and field names with automated mapping and alerting.
AI & Agentic Intelligence
Uses Generative AI to generate validation logic and Agentic AI modules to orchestrate data audits.
Data Quality Assurance
Identifies duplicates, nulls, missing fields, and default value anomalies in migrated data
Real-time Dashboards & Reports
Offers visual insights, exception reports, and reconciliation summaries for stakeholders.
Audit & Compliance Ready
Generates detailed audit trails and supports regulatory compliance through standardized reports.
Benefits:
Up to 90% of time saving : Automation significantly reduces reconciliation time compared to manual efforts
Up to 90% of cost reduction : Significantly reduces resources for Testing and QA team and reduce costs using DataReconRemit reconciliation tool.
Up to 90% increased reconciliation accuracy : The Framework processes the full data set which improve the reconciliation accuracy up to 90%
Greater visibility and less dependency on staff: Centralized dashboards offer real-time insights into data integrity, reconciliation status, and anomalies. Self-Service tools.