AI Statement Reconciliation Agent

Reconcile in minutes, not weeks

Reconcile in minutes, not weeks

Delegate the tedious task of reconciliation to a specialized AI agent. It intelligently compares thousands of transactions between any two systems—like a bank statement and your GL—and automatically produces a clean exception report, so your team can focus on investigating, not ticking.

Why V7 Go

Why V7 Go

Intelligent Transaction Matching

Goes beyond exact matches. The agent uses AI to match transactions based on amount, date proximity, and fuzzy text matching on descriptions, dramatically increasing the automated match rate.

Intelligent Transaction Matching

Goes beyond exact matches. The agent uses AI to match transactions based on amount, date proximity, and fuzzy text matching on descriptions, dramatically increasing the automated match rate.

Intelligent Transaction Matching

Goes beyond exact matches. The agent uses AI to match transactions based on amount, date proximity, and fuzzy text matching on descriptions, dramatically increasing the automated match rate.

Handles Any Data Source

Reconciles data from any two sources, whether it's a scanned PDF bank statement against an ERP export, or a custodial statement against your internal portfolio management system.

Handles Any Data Source

Reconciles data from any two sources, whether it's a scanned PDF bank statement against an ERP export, or a custodial statement against your internal portfolio management system.

Handles Any Data Source

Reconciles data from any two sources, whether it's a scanned PDF bank statement against an ERP export, or a custodial statement against your internal portfolio management system.

Complex Matching Logic

Configurable for complex scenarios, such as one-to-many matches (e.g., one bank deposit matching multiple invoices) and many-to-many reconciliations.

Complex Matching Logic

Configurable for complex scenarios, such as one-to-many matches (e.g., one bank deposit matching multiple invoices) and many-to-many reconciliations.

Complex Matching Logic

Configurable for complex scenarios, such as one-to-many matches (e.g., one bank deposit matching multiple invoices) and many-to-many reconciliations.

Automated Exception Reporting

Saves your team hours of searching. The agent's primary output is a clean, concise report of only the items that *didn't* match, so your team can focus exclusively on investigation.

Automated Exception Reporting

Saves your team hours of searching. The agent's primary output is a clean, concise report of only the items that *didn't* match, so your team can focus exclusively on investigation.

Automated Exception Reporting

Saves your team hours of searching. The agent's primary output is a clean, concise report of only the items that *didn't* match, so your team can focus exclusively on investigation.

Suggested Reconciling Items

Based on your rules, the agent can automatically identify and categorize common reconciling items like bank fees, interest income, and outstanding checks, further speeding up the process.

Suggested Reconciling Items

Based on your rules, the agent can automatically identify and categorize common reconciling items like bank fees, interest income, and outstanding checks, further speeding up the process.

Suggested Reconciling Items

Based on your rules, the agent can automatically identify and categorize common reconciling items like bank fees, interest income, and outstanding checks, further speeding up the process.

Creates an Auditable Workflow

Generates a complete, auditable reconciliation workpaper that shows the full populations, the items that were automatically matched, and the resolution of every exception.

Creates an Auditable Workflow

Generates a complete, auditable reconciliation workpaper that shows the full populations, the items that were automatically matched, and the resolution of every exception.

Creates an Auditable Workflow

Generates a complete, auditable reconciliation workpaper that shows the full populations, the items that were automatically matched, and the resolution of every exception.

Why V7 Go

Intelligently compares transactions from any two sources

To produce a perfect reconciliation in minutes.

Workflow

Workflow

QuickBooks
QuickBooks
QuickBooks
QuickBooks

Import your files

QuickBooks

,

NetSuite

,

Microsoft Excel

Time comparison

Time comparison

Time comparison

Time comparison

Traditional way

Days per month

Days per month

With V7 Go agents

Minutes

Minutes

Average time saved

99%

99%

V7 Go

V7 Go

V7 Go

V7 Go

Turn your most tedious monthly task

into a fast, automated workflow

Reconciling statements is a universal accounting headache and a major cause of the month-end crunch. Accountants and operations teams are drowning in the manual, line-by-line 'tick and tie' process of matching transactions between bank or custodial statements and their internal book of record. This is not the impactful work you hired your team for. It's slow, prone to human error, and a major reason why the financial close takes weeks instead of days. For the tedious work you hate, there's V7 Go.

Accounting & Controllership

Dramatically accelerate your month-end close. Automate the manual 'tick and tie' process to free up your accountants to focus on investigating exceptions and performing high-value analysis.

Accounting & Controllership

Dramatically accelerate your month-end close. Automate the manual 'tick and tie' process to free up your accountants to focus on investigating exceptions and performing high-value analysis.

Accounting & Controllership

Dramatically accelerate your month-end close. Automate the manual 'tick and tie' process to free up your accountants to focus on investigating exceptions and performing high-value analysis.

Accounting & Controllership

Dramatically accelerate your month-end close. Automate the manual 'tick and tie' process to free up your accountants to focus on investigating exceptions and performing high-value analysis.

Family Offices & Fund Administrators

Bring efficiency and scale to your operations. Automate the reconciliation of dozens or hundreds of complex accounts to ensure accuracy, improve client reporting, and reduce operational risk.

Family Offices & Fund Administrators

Bring efficiency and scale to your operations. Automate the reconciliation of dozens or hundreds of complex accounts to ensure accuracy, improve client reporting, and reduce operational risk.

Family Offices & Fund Administrators

Bring efficiency and scale to your operations. Automate the reconciliation of dozens or hundreds of complex accounts to ensure accuracy, improve client reporting, and reduce operational risk.

Family Offices & Fund Administrators

Bring efficiency and scale to your operations. Automate the reconciliation of dozens or hundreds of complex accounts to ensure accuracy, improve client reporting, and reduce operational risk.

More automations

Other automations

Transform your business
with other AI Agents

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More agents

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Qualitative Screening

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Automate your private equity deal sourcing. This V7 Go agent monitors the market for your custom investment triggers to find proprietary, off-market investment opportunities.

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Qualitative Screening

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Accelerate your PE deal process. This V7 Go agent automates due diligence by analyzing data rooms, extracting financials, summarizing risks, and drafting investment memos.

Private Equity Due Diligence

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Accelerate your PE deal process. This V7 Go agent automates due diligence by analyzing data rooms, extracting financials, summarizing risks, and drafting investment memos.

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Welcome Go

Welcome Go

Welcome Go

Welcome Go

Reconcile in minutes, not weeks

Reconcile in minutes, not weeks

Reconcile in minutes, not weeks

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

FAQ

FAQ

FAQ

FAQ

Have questions?
Find answers.

Our custodial statements are all in different PDF formats. How does it handle that?

This agent is typically chained with our Statement Processing Agent. That agent first reads and extracts the raw transaction data from all the inconsistent PDF formats into a single, standardized spreadsheet. This agent then performs the reconciliation on that clean data.

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Our custodial statements are all in different PDF formats. How does it handle that?

This agent is typically chained with our Statement Processing Agent. That agent first reads and extracts the raw transaction data from all the inconsistent PDF formats into a single, standardized spreadsheet. This agent then performs the reconciliation on that clean data.

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Our custodial statements are all in different PDF formats. How does it handle that?

This agent is typically chained with our Statement Processing Agent. That agent first reads and extracts the raw transaction data from all the inconsistent PDF formats into a single, standardized spreadsheet. This agent then performs the reconciliation on that clean data.

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Our custodial statements are all in different PDF formats. How does it handle that?

This agent is typically chained with our Statement Processing Agent. That agent first reads and extracts the raw transaction data from all the inconsistent PDF formats into a single, standardized spreadsheet. This agent then performs the reconciliation on that clean data.

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What kind of systems can it reconcile?

It can reconcile any two systems that can produce a list of transactions. This includes bank accounts, credit cards, custodial accounts, portfolio management systems, and your internal general ledger or accounting software.

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What kind of systems can it reconcile?

It can reconcile any two systems that can produce a list of transactions. This includes bank accounts, credit cards, custodial accounts, portfolio management systems, and your internal general ledger or accounting software.

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What kind of systems can it reconcile?

It can reconcile any two systems that can produce a list of transactions. This includes bank accounts, credit cards, custodial accounts, portfolio management systems, and your internal general ledger or accounting software.

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What kind of systems can it reconcile?

It can reconcile any two systems that can produce a list of transactions. This includes bank accounts, credit cards, custodial accounts, portfolio management systems, and your internal general ledger or accounting software.

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How does the 'fuzzy matching' work?

It uses AI algorithms to find likely matches even when the text isn't identical. For example, it can learn that a bank description of 'ACH PYMT Amazon Web Services' should match a GL entry for 'AWS Cloud Hosting Fee' if the date and amount are close.

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How does the 'fuzzy matching' work?

It uses AI algorithms to find likely matches even when the text isn't identical. For example, it can learn that a bank description of 'ACH PYMT Amazon Web Services' should match a GL entry for 'AWS Cloud Hosting Fee' if the date and amount are close.

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How does the 'fuzzy matching' work?

It uses AI algorithms to find likely matches even when the text isn't identical. For example, it can learn that a bank description of 'ACH PYMT Amazon Web Services' should match a GL entry for 'AWS Cloud Hosting Fee' if the date and amount are close.

+

How does the 'fuzzy matching' work?

It uses AI algorithms to find likely matches even when the text isn't identical. For example, it can learn that a bank description of 'ACH PYMT Amazon Web Services' should match a GL entry for 'AWS Cloud Hosting Fee' if the date and amount are close.

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What is the final output of the reconciliation?

The agent delivers a comprehensive reconciliation package, typically in Excel. This includes a list of all matched items, a clean, prioritized list of all unmatched exceptions, and a summary that proves the two systems are in balance.

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What is the final output of the reconciliation?

The agent delivers a comprehensive reconciliation package, typically in Excel. This includes a list of all matched items, a clean, prioritized list of all unmatched exceptions, and a summary that proves the two systems are in balance.

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What is the final output of the reconciliation?

The agent delivers a comprehensive reconciliation package, typically in Excel. This includes a list of all matched items, a clean, prioritized list of all unmatched exceptions, and a summary that proves the two systems are in balance.

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What is the final output of the reconciliation?

The agent delivers a comprehensive reconciliation package, typically in Excel. This includes a list of all matched items, a clean, prioritized list of all unmatched exceptions, and a summary that proves the two systems are in balance.

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Can it suggest the journal entries needed to fix the exceptions?

Yes. Based on your predefined rules for common reconciling items (like bank fees), the agent can be configured to suggest the correct adjusting journal entries for your team to review and post.

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Can it suggest the journal entries needed to fix the exceptions?

Yes. Based on your predefined rules for common reconciling items (like bank fees), the agent can be configured to suggest the correct adjusting journal entries for your team to review and post.

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Can it suggest the journal entries needed to fix the exceptions?

Yes. Based on your predefined rules for common reconciling items (like bank fees), the agent can be configured to suggest the correct adjusting journal entries for your team to review and post.

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Can it suggest the journal entries needed to fix the exceptions?

Yes. Based on your predefined rules for common reconciling items (like bank fees), the agent can be configured to suggest the correct adjusting journal entries for your team to review and post.

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How can our auditors trust an AI-powered reconciliation?

Through a transparent and auditable process. The agent 'shows its work' with a complete log of which items it matched and why. Because the underlying data is extracted with visual citations, you have a complete, verifiable trail from start to finish.

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How can our auditors trust an AI-powered reconciliation?

Through a transparent and auditable process. The agent 'shows its work' with a complete log of which items it matched and why. Because the underlying data is extracted with visual citations, you have a complete, verifiable trail from start to finish.

+

How can our auditors trust an AI-powered reconciliation?

Through a transparent and auditable process. The agent 'shows its work' with a complete log of which items it matched and why. Because the underlying data is extracted with visual citations, you have a complete, verifiable trail from start to finish.

+

How can our auditors trust an AI-powered reconciliation?

Through a transparent and auditable process. The agent 'shows its work' with a complete log of which items it matched and why. Because the underlying data is extracted with visual citations, you have a complete, verifiable trail from start to finish.

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