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Power Reconcile

AI Automated Accounting

Power Reconciliation is a AI automated data cleaning, fuzzy compare and merge, and automated reconciliation toolset available as one of many premium apps available for Power Sheet Enterprise which you can embed into any Excel spreadsheet install-free

Power Reconciliation - AI Powered Data P

Key Benefits

AI-Automated Find & Fix, Fuzzy Matching, Deduplication and Reporting

Find, fix & report discrepancies and errors in data across all rows and columns across multiple Excel spreadsheets, data sources, and types of reports.

This is accomplished with cutting-edge AI which automates cross-referencing with intelligent fuzzy matching, mot only for names (contacts, clients, accounts, vendors) but also for numbers and even combinations of records & numbers as well. 

AI Learns & Remembers Corrections, Data Prep, Replacements & Transformations

In addition to flexible, customizable, auto-generated reports, Power Reconciliation can also automatically match up, categorize, de-duplicate and fix errors, while remembering and learning from your corrections to apply to future data sets, or preserve mappings and other transformations.

Ad-hoc, Self-Service Matching, Fixes, AI & Deduplication  Online and in Excel

It can be used for ad-hoc analysis, de-duplication, and AI automated finding, fixing of errors together with financial & accounting software systems, through its Artificial Intelligence powered intelligent handling.

Use with Excel, QuickBooks and Leading Financial, Accounting, CRM & Other Systems

It provides out-of-box templates and support for, leading financial, accounting, reporting, bookkeeping, banking, analytics, financial close, analytics and management software, systems and vendors. It's AI can also automatically interpret and suggest how to handle data from any source, even when templates and apps aren't already provided, and its AI allows you to easily build, save and reuse your own apps, data prep and transformations.

Workflow Automation

Power Reconciliation is designed to automate workflows, reporting, analysis, and finding and fixing, merging, matching or reporting on discrepancies, duplicates, near matches, misspellings, variance and other errors in data, with systems and use cases





  • Power - Columns - cycles EVERY combination of columns to create hierarchy of matches. Will deliver 1-to-many or many-to-many matches if enough common information, like 1 check number in bank statement is same as 5 of same check numbers in internal records that sum to same amount

  • Power - Rows - cycles every combination of Rows until balances match.   It can match partial payments with bills by looking at series of payments and figuring out which ones apply to which bills.

  • Artificial Intelligence - for Pay-As-You-Go picks most important columns and even adds an amount column if only debit and credit are included

  • Import from Clipboard, CSV, Excel - data is only in the browser. It NEVER goes to any server. Complete privacy and security is maintained

  • Export to Clipboard, CSV, Excel - every view and table created can be exported to any program.

  • Row Filters - filter unwanted date ranges (Pay-As-You-Go users must manually filter before import)

  • Add Calculated Columns - More than 20 special columns that can be added to assist in analysis

  • Fuzzy matching - Match multiple spellings of same name, like Dan's Bar, Dans Bar Dan's Grill, Dan's BBQ

  • Deduplication - Find near matches like and and  It not only matches TWO sets of data, it keeps digging for more and more near matches.   

  • Save/Open Environment - Everything is stored in the browser but users can save their entire working environment to their local hard drive. Email. Dropbox. Share with others. Then continue.

  • Notation and Reporting - Every match and number can be notated and scored so users can focus on problematic data and others receiving the data can understand work already completed.

  • Reconciliation Dashboard - Enter beginning and ending balances and see reconciliation with breakdown by quality of matches.

  • 1-to-Many and Many-to-Many by Dates - Reconciles transactions like vendor bills and partial payments and complex payroll entries with 3 bank disbursements and 5 journal entries.

  • Manual Matching - Users often need to manually match or notate data, for example, disbursements shown on a bank statement that were recorded internally in prior period

  • Fraud Analysis - Prepare for audit and due diligence. Defense against internal malfeasance. Ghost Accounts - Bad actors may multiple vendors with similar names to hide disbursements Sequence Errors - Spot missing items that should be in a sequence Anomalous disbursements - highlight vendors with strange disbursement patterns

  • Record Find and Replace - You can find and replace data like with Excel (it's actually more powerful).  But on top of that, it records all of the steps and you can replay the same steps with a new set of data.  It's a little bit like a macro, but just for edits.

  • Automation - Set up apps that walk users precisely through steps to desired outcome .  The apps can prompt users for information.


Auto Find, Fix, Dedupe and Matching


  • Transactions that don't exactly match bank statements.   

  • Near duplicates like Dan's Bar and Grill and Dan's Bar & Grill.

  • Intercompany transactions that are missing on one side of the ledger.

  • Bills with missing payments (match partial payments against bills)

  • Last minute changes in a ledger that's throwing off balances.


AI Automated Finance, Data, Reconciliation, Reporting and Analytics

  • Months or years of bank history with X thousands of transactions.

  • Customer lists, vendor lists, comparing accounting to CRM data.

  • Data with grouped transactions that needs to be compared to details.

  • Payroll reports with many rows compared to grouped bank data.

  • Thousands of rows of trial balance data compared to earlier versions.

How does work?

  1. Artificial intelligence scans haystacks with tremendous precision.   It will MATCH the combination of D. Smith, Doug Smith, and Douglas Smith on one side,  with activity that sums to 1,000 with Douglas H. Smith on the other side, that also sums to 1,000.  Four different spellings!

  2. AI that matches ACH transfers on a Friday with bank transactions that arrive on the following Monday.

  3. Intelligence that looks at every combination of every column to look for the best matches (meaning the ones with the most matching columns) and then methodically identifying matches of lesser quality.   And enabling the user to identify each segment of the haystack.

  4. It matches data in smart ways.  Not just the simple, Brian = Brian, but it also knows that Bryan and Brian are about 80% the same.  Its calculations, artificial intelligence, and automation are proprietary and unique.  

  5. To search a haystack, segregate sections and check them one by one. does something similar.  It dissects the haystack, using Artificial Intelligence, to rank the quality of the matches.  So, in effect, produces a report card on each section of the haystack.  It doesn't just find needles.  It dissects the quality of the entire haystack.

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