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Use Case

Data Reconciliation

47,000 records processed. 23 discrepancies found. 0.05% error rate - caught before month-end close.

The Problem

You have the same data in three systems: your ERP, your CRM, and your data warehouse. And every month, they don't match. Your finance team exports everything to Excel, writes VLOOKUP formulas, and spends a week hunting for the $0.02 difference that's preventing close.

The real cost isn't the time - it's the errors you miss. A customer marked active in Salesforce but inactive in your billing system. An invoice posted twice. A payment applied to the wrong account. By the time you find them, the damage is done.

The Automation

Our reconciliation agent connects to any system with an API or database access. It compares records across systems using fuzzy matching, learns your business rules, and flags only the exceptions that need human judgment.

01

Extract

Pulls data from source systems on schedule or on-demand

02

Match

AI correlates records across systems using keys, fuzzy logic, and business rules

03

Validate

Checks for missing records, field mismatches, and out-of-range values

04

Report

Generates exception reports with suggested resolutions and routes to owners

Data reconciliation dashboard showing error detection across records
99.9%Accuracy
40 hrsSaved monthly
3 daysFaster close

Types of Errors Caught

  • Missing records - Transaction in System A, no corresponding record in System B
  • Field mismatches - Same record, different values (amounts, dates, statuses)
  • Orphaned data - Child records without parent records
  • Duplicate detection - Same transaction recorded multiple times
  • Referential integrity - Invalid foreign keys, inactive customers with open orders

Real Results

"We reconciled 50,000 customer records across three systems in 2 hours. The agent found 147 discrepancies our manual process missed for months. Month-end close went from 8 days to 5."
- Controller, B2B software company

Any Data, Any System

FlowRunner reconciles across:

  • Databases (PostgreSQL, MySQL, SQL Server, Oracle)
  • Cloud apps (Salesforce, NetSuite, HubSpot, Stripe)
  • Files (CSV, Excel, XML, JSON)
  • APIs (REST, GraphQL, SOAP)
  • Data warehouses (Snowflake, BigQuery, Redshift)

Find your data errors

Run a free reconciliation analysis on your critical data sets. See what you've been missing.

Request analysis