AI-powered fuzzy matching, and assigns confidence scores.

Overview This workflow automates financial reconciliation across multiple data sources such as bank statements, invoices, ERP systems, and CSV uploads.

It standardizes all incoming data, performs rule-based matching, enhances results with AI-powered fuzzy matching, and assigns confidence scores. High-confidence matches are auto-reconciled, while uncertain ones are flagged for human review.

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How It Works

1. Data Ingestion Receives financial data via webhook from different sources.

2. Source Detection & Routing Identifies the data type and routes it to the correct normalization flow.

3. Data Normalization Converts all records into a unified schema with consistent fields like ID, amount, date, and description.

4. Data Merging Combines all normalized records into a single dataset for matching.