90% faster credit analysis
AI agent for Municipal Bond Analysts
From document chaos to credit clarity
Delegate municipal credit research to a specialized AI agent. It reads official statements, comprehensive annual financial reports, and local government budgets to extract debt ratios, fund balances, revenue trends, and pension obligations—delivering standardized credit metrics regardless of document format.

Ideal for
Municipal Bond Analysts
Fixed Income Research
Credit Rating Agencies

See AI agent for Municipal Bond Analysts in action
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Springfield County Credit Review
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Time comparison
Time comparison
Traditional way
3-5 hours per issuer
With V7 Go agents
15-20 minutes
Average time saved
90%
Why V7 Go
Why V7 Go
Automated Financial Metric Extraction
Pulls debt service coverage ratios, fund balance percentages, revenue growth rates, and liquidity metrics from any government financial document, regardless of format or presentation style.
Automated Financial Metric Extraction
Pulls debt service coverage ratios, fund balance percentages, revenue growth rates, and liquidity metrics from any government financial document, regardless of format or presentation style.
Automated Financial Metric Extraction
Pulls debt service coverage ratios, fund balance percentages, revenue growth rates, and liquidity metrics from any government financial document, regardless of format or presentation style.
Automated Financial Metric Extraction
Pulls debt service coverage ratios, fund balance percentages, revenue growth rates, and liquidity metrics from any government financial document, regardless of format or presentation style.
Multi-Year Trend Analysis
Tracks financial indicators across multiple fiscal years by processing historical CAFRs and budget documents, identifying deteriorating credit conditions before they become critical.
Multi-Year Trend Analysis
Tracks financial indicators across multiple fiscal years by processing historical CAFRs and budget documents, identifying deteriorating credit conditions before they become critical.
Multi-Year Trend Analysis
Tracks financial indicators across multiple fiscal years by processing historical CAFRs and budget documents, identifying deteriorating credit conditions before they become critical.
Multi-Year Trend Analysis
Tracks financial indicators across multiple fiscal years by processing historical CAFRs and budget documents, identifying deteriorating credit conditions before they become critical.
Pension and OPEB Liability Assessment
Extracts unfunded actuarial accrued liability figures, funded ratios, and annual required contributions from actuarial reports embedded within comprehensive financial statements.
Pension and OPEB Liability Assessment
Extracts unfunded actuarial accrued liability figures, funded ratios, and annual required contributions from actuarial reports embedded within comprehensive financial statements.
Pension and OPEB Liability Assessment
Extracts unfunded actuarial accrued liability figures, funded ratios, and annual required contributions from actuarial reports embedded within comprehensive financial statements.
Pension and OPEB Liability Assessment
Extracts unfunded actuarial accrued liability figures, funded ratios, and annual required contributions from actuarial reports embedded within comprehensive financial statements.
Revenue Concentration Detection
Identifies reliance on volatile revenue sources by analyzing tax base composition, intergovernmental transfers, and enterprise fund performance across government-wide financial statements.
Revenue Concentration Detection
Identifies reliance on volatile revenue sources by analyzing tax base composition, intergovernmental transfers, and enterprise fund performance across government-wide financial statements.
Revenue Concentration Detection
Identifies reliance on volatile revenue sources by analyzing tax base composition, intergovernmental transfers, and enterprise fund performance across government-wide financial statements.
Revenue Concentration Detection
Identifies reliance on volatile revenue sources by analyzing tax base composition, intergovernmental transfers, and enterprise fund performance across government-wide financial statements.
Debt Structure Normalization
Standardizes debt metrics by extracting direct debt, overlapping debt, and contingent liabilities from notes to financial statements, creating comparable leverage ratios across issuers.
Debt Structure Normalization
Standardizes debt metrics by extracting direct debt, overlapping debt, and contingent liabilities from notes to financial statements, creating comparable leverage ratios across issuers.
Debt Structure Normalization
Standardizes debt metrics by extracting direct debt, overlapping debt, and contingent liabilities from notes to financial statements, creating comparable leverage ratios across issuers.
Debt Structure Normalization
Standardizes debt metrics by extracting direct debt, overlapping debt, and contingent liabilities from notes to financial statements, creating comparable leverage ratios across issuers.
Verifiable Data Lineage
Links every extracted financial figure to its exact location in the source document with AI Citations, providing auditable evidence for credit committee presentations and rating agency discussions.
Verifiable Data Lineage
Links every extracted financial figure to its exact location in the source document with AI Citations, providing auditable evidence for credit committee presentations and rating agency discussions.
Verifiable Data Lineage
Links every extracted financial figure to its exact location in the source document with AI Citations, providing auditable evidence for credit committee presentations and rating agency discussions.
Verifiable Data Lineage
Links every extracted financial figure to its exact location in the source document with AI Citations, providing auditable evidence for credit committee presentations and rating agency discussions.
Extracts credit metrics from any government document
To deliver standardized issuer analysis.
Get started
Get started



Import your files
Microsoft Excel
,
Snowflake
,
Tableau
Import your files from whereever they are currently stored
All types of Finance documents supported
Once imported our system extracts and organises the essentials
Customer voices
Customer voices
Connect AI to your credit framework.
Connect AI to your credit framework.
Turn government documents into standardized credit metrics.
Turn government documents into standardized credit metrics.
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Customer Voices
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Industrial equipment sales
We are looking for V7 Go and AI in general to be the beating heart of our company and our growth. It will make us more productive as a company, liaising with customers, automating tasks, even finding new work.
Read the full story
Insurance
We have six assessors. Before V7 Go, each would process around 15 claims a day, about 90 in total. With V7 Go, we’re expecting that to rise to around 20 claims per assessor, which adds up to an extra 30 claims a day. That’s the equivalent of two additional full-time assessors. Beyond the cost savings, there’s real reputational gains from fewer errors and faster turnaround times.
Read the full story
Real Estate
Prior to V7, people using the software were manually inputting data. Now it’s so much faster because it just reads it for them. On average, it saves our customers 45 minutes to an hour of work, and it’s more accurate.
Read the full story
Finance
“Whenever I think about hiring, I first try to do it in V7 Go.” Discover how HITICCO uses V7 Go agents to accelerate and enrich their prospect research.
Read the full story
Finance
The experience with V7 has been fantastic. Very customized level of support. You feel like they really care about your outcome and objectives.
Read the full story
Features
Features
Results you can actually trust.
Reliable AI document processing toolkit.
Results you can trust.
Trustworthy AI document processing toolkit.
Supporting complex documents.
Up to 200 pages.
Municipal financial documents vary wildly in structure and format. This agent handles comprehensive annual financial reports with embedded actuarial valuations, budget presentations with multi-year projections, and official statements with complex debt schedules—extracting metrics regardless of layout.
Input types
50+ languages
Complex Tables
200 pages
Multi-modal
Document types
PDFs
Scanned Documents
Financial Tables
Charts
Spreadsheets
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.
Up to 200 pages.
Municipal financial documents vary wildly in structure and format. This agent handles comprehensive annual financial reports with embedded actuarial valuations, budget presentations with multi-year projections, and official statements with complex debt schedules—extracting metrics regardless of layout.
Input types
50+ languages
Complex Tables
200 pages
Multi-modal
Document types
PDFs
Scanned Documents
Financial Tables
Charts
Spreadsheets
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.
Up to 200 pages.
Municipal financial documents vary wildly in structure and format. This agent handles comprehensive annual financial reports with embedded actuarial valuations, budget presentations with multi-year projections, and official statements with complex debt schedules—extracting metrics regardless of layout.
Input types
50+ languages
Complex Tables
200 pages
Multi-modal
Document types
PDFs
Scanned Documents
Financial Tables
Charts
Spreadsheets
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate
through GenAI reasoning.
Credit decisions depend on precise financial data. The agent uses multi-step verification to ensure debt ratios, fund balances, and revenue figures are extracted with exceptional accuracy, cross-referencing numbers across related statements to catch inconsistencies.
Model providers

Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Reach 99% accuracy rate
through GenAI reasoning.
Credit decisions depend on precise financial data. The agent uses multi-step verification to ensure debt ratios, fund balances, and revenue figures are extracted with exceptional accuracy, cross-referencing numbers across related statements to catch inconsistencies.
Model providers

Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Reach 99% accuracy rate
through GenAI reasoning.
Credit decisions depend on precise financial data. The agent uses multi-step verification to ensure debt ratios, fund balances, and revenue figures are extracted with exceptional accuracy, cross-referencing numbers across related statements to catch inconsistencies.
Model providers

Security note
V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.
Answer
Type
Text
Tool
o4 Mini
Reasoning effort
Min
Low
Mid
High
AI Citations
Inputs
Set a prompt (Press @ to mention an input)
Trustworthy results,
grounded in reality.
Build confidence in your credit analysis. Every extracted metric is visually linked to its source location in the financial statement, providing instant verification for credit committee presentations and regulatory examinations.

Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance

02
01
01
02
Trustworthy results,
grounded in reality.
Build confidence in your credit analysis. Every extracted metric is visually linked to its source location in the financial statement, providing instant verification for credit committee presentations and regulatory examinations.

Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance

02
01
01
02
Trustworthy results,
grounded in reality.
Build confidence in your credit analysis. Every extracted metric is visually linked to its source location in the financial statement, providing instant verification for credit committee presentations and regulatory examinations.

Visual grounding in action
00:54
Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.
Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.
Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.
Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.
Prior Warning and Ignoring Compliance

02
01
01
02
Enterprise grade security
for high-stake industries.
Municipal financial analysis involves material non-public information during new issue periods. V7 Go processes all documents within your secure environment, ensuring compliance with securities regulations and maintaining confidentiality of pre-release financial data.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Municipal financial analysis involves material non-public information during new issue periods. V7 Go processes all documents within your secure environment, ensuring compliance with securities regulations and maintaining confidentiality of pre-release financial data.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise grade security
for high-stake industries.
Municipal financial analysis involves material non-public information during new issue periods. V7 Go processes all documents within your secure environment, ensuring compliance with securities regulations and maintaining confidentiality of pre-release financial data.
Certifications
GPDR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
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Answers
Answers
What you need to know about our
AI agent for Municipal Bond Analysts
How does it handle different government accounting formats?
The agent is designed to process GASB-compliant financial statements regardless of presentation format. It understands fund accounting structures, government-wide statements, and the relationship between different financial statement components, adapting to each issuer's unique reporting style.
+
How does it handle different government accounting formats?
The agent is designed to process GASB-compliant financial statements regardless of presentation format. It understands fund accounting structures, government-wide statements, and the relationship between different financial statement components, adapting to each issuer's unique reporting style.
+
How does it handle different government accounting formats?
The agent is designed to process GASB-compliant financial statements regardless of presentation format. It understands fund accounting structures, government-wide statements, and the relationship between different financial statement components, adapting to each issuer's unique reporting style.
+
Can it analyze both general obligation and revenue bonds?
Yes. The agent extracts metrics relevant to both security types. For general obligation bonds, it focuses on tax base and general fund metrics. For revenue bonds, it analyzes enterprise fund performance, debt service coverage, and project-specific financial data.
+
Can it analyze both general obligation and revenue bonds?
Yes. The agent extracts metrics relevant to both security types. For general obligation bonds, it focuses on tax base and general fund metrics. For revenue bonds, it analyzes enterprise fund performance, debt service coverage, and project-specific financial data.
+
Can it analyze both general obligation and revenue bonds?
Yes. The agent extracts metrics relevant to both security types. For general obligation bonds, it focuses on tax base and general fund metrics. For revenue bonds, it analyzes enterprise fund performance, debt service coverage, and project-specific financial data.
+
What types of documents can it process?
The agent processes official statements, comprehensive annual financial reports, adopted budgets, quarterly financial updates, continuing disclosure filings, and actuarial valuation reports. It handles both current year documents and historical archives for trend analysis.
+
What types of documents can it process?
The agent processes official statements, comprehensive annual financial reports, adopted budgets, quarterly financial updates, continuing disclosure filings, and actuarial valuation reports. It handles both current year documents and historical archives for trend analysis.
+
What types of documents can it process?
The agent processes official statements, comprehensive annual financial reports, adopted budgets, quarterly financial updates, continuing disclosure filings, and actuarial valuation reports. It handles both current year documents and historical archives for trend analysis.
+
How accurate is the financial data extraction?
The agent uses multi-step verification workflows to ensure numerical accuracy. Every extracted figure is cross-referenced against related statements and reconciled to totals. Visual Grounding allows analysts to verify any number by clicking through to the source page.
+
How accurate is the financial data extraction?
The agent uses multi-step verification workflows to ensure numerical accuracy. Every extracted figure is cross-referenced against related statements and reconciled to totals. Visual Grounding allows analysts to verify any number by clicking through to the source page.
+
How accurate is the financial data extraction?
The agent uses multi-step verification workflows to ensure numerical accuracy. Every extracted figure is cross-referenced against related statements and reconciled to totals. Visual Grounding allows analysts to verify any number by clicking through to the source page.
+
Does it understand footnote disclosures?
Absolutely. The agent reads and interprets notes to financial statements, extracting critical information about debt covenants, contingent liabilities, subsequent events, and accounting policy changes that impact credit quality assessment.
+
Does it understand footnote disclosures?
Absolutely. The agent reads and interprets notes to financial statements, extracting critical information about debt covenants, contingent liabilities, subsequent events, and accounting policy changes that impact credit quality assessment.
+
Does it understand footnote disclosures?
Absolutely. The agent reads and interprets notes to financial statements, extracting critical information about debt covenants, contingent liabilities, subsequent events, and accounting policy changes that impact credit quality assessment.
+
What is the final output format?
The agent delivers a structured dataset containing standardized credit metrics, typically in Excel or JSON format. This output can be configured to match your internal credit models or populate directly into your fixed income research management system.
+
What is the final output format?
The agent delivers a structured dataset containing standardized credit metrics, typically in Excel or JSON format. This output can be configured to match your internal credit models or populate directly into your fixed income research management system.
+
What is the final output format?
The agent delivers a structured dataset containing standardized credit metrics, typically in Excel or JSON format. This output can be configured to match your internal credit models or populate directly into your fixed income research management system.
+
Next steps
Next steps
Still manually extracting data from CAFRs and official statements?
Send us a few municipal financial reports from your coverage universe. We'll show you how our AI agent can deliver standardized credit metrics in minutes instead of hours.
Uncover hidden liabilities
in
supplier contracts.
V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:
Uncover hidden liabilities
in
supplier contracts.
V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:
