Your Team Spends Friday Afternoons Reconciling Spreadsheets

Every month, someone manually matches transactions across systems, hunts down discrepancies, and builds the reconciliation report. We build AI that does it overnight.

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90%
Less reconciliation time
0
Manual matching required
Real-time
Exception flagging
$60K
Avg annual savings
01
Document Arrives
02
AI Extracts & Validates
03
Routed & Done

Results from Similar Implementations

90%
Less reconciliation time
0
Manual matching required
Real-time
Exception flagging
$60K
Avg annual savings

Frequently Asked Questions

How does the AI match transactions across different systems?
The system ingests data from all your financial sources — accounting software, bank feeds, billing platforms, POS systems, project management tools — normalizes the formats, and applies matching rules specific to your business. Exact matches clear automatically. Fuzzy matches (partial amounts, date offsets, split transactions) get flagged with context so your team resolves them in minutes instead of hours. The matching rules improve over time as the system learns your patterns.
What if our data lives in spreadsheets and legacy systems?
That's the norm, not the exception. Most clients we work with have financial data spread across 3-8 systems, with at least one being a spreadsheet someone emails around on Fridays. The AI connects to whatever you have — APIs for modern systems, file watchers for exports, even email attachment parsing for the stubborn ones. We build around your reality, not an ideal state.
How long does it take to set up?
The assessment takes 1 week and identifies where the reconciliation bottlenecks are. The build typically runs 6-10 weeks depending on how many source systems need connecting. Most clients see the first automated reconciliation within 60 days of starting the build. We deploy in 2-week sprints, so you see progress continuously.
Can it handle our industry-specific reconciliation rules?
Every implementation is custom-built for your business rules. Construction retainage schedules, hotel night audit procedures, legal trust account compliance, club dues allocation — these aren't generic rules we configure from a dropdown. We map your specific reconciliation logic into the system during the assessment phase and build it to match exactly how your business operates.
What happens when the AI gets something wrong?
Every transaction match includes a confidence score. High-confidence matches clear automatically. Anything below threshold routes to a human reviewer with full context — the source records, the match reason, and a recommended action. Your team makes the judgment call. Over time, the threshold adjusts as the system learns. Error rates typically drop below 1% within the first 90 days.

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