AI Business Analytics Agent
Pull metrics from all your systems and documents
Pull metrics from all your systems and documents
V7 Go's AI business analytics agent connects to Salesforce, Hubspot, QuickBooks, ERP systems, databases, and documents to extract revenue growth, CAC, NPS scores, and other KPIs. Get consistent metrics regardless of where your data lives.
Why V7 Go
Why V7 Go
KPI Tracking
Extract key performance indicators from multiple sources including CRM records, ERP data, financial systems, databases, and business documents. The AI agent creates consistent measurement of revenue growth, profit margins, and customer metrics across platforms and time periods.
KPI Tracking
Extract key performance indicators from multiple sources including CRM records, ERP data, financial systems, databases, and business documents. The AI agent creates consistent measurement of revenue growth, profit margins, and customer metrics across platforms and time periods.
KPI Tracking
Extract key performance indicators from multiple sources including CRM records, ERP data, financial systems, databases, and business documents. The AI agent creates consistent measurement of revenue growth, profit margins, and customer metrics across platforms and time periods.
Trend Analysis
AI-powered identification of patterns by analyzing data across disconnected systems and formats. Detect emerging trends in customer behavior, sales performance, and operational efficiency that remain hidden when looking at individual data sources in isolation.
Trend Analysis
AI-powered identification of patterns by analyzing data across disconnected systems and formats. Detect emerging trends in customer behavior, sales performance, and operational efficiency that remain hidden when looking at individual data sources in isolation.
Trend Analysis
AI-powered identification of patterns by analyzing data across disconnected systems and formats. Detect emerging trends in customer behavior, sales performance, and operational efficiency that remain hidden when looking at individual data sources in isolation.
Performance Measurement
Compare actual results against forecasts, budgets, and prior periods by pulling data from planning systems, financial platforms, and reporting tools. The AI agent standardizes calculations to eliminate inconsistencies in how different departments measure the same metrics.
Performance Measurement
Compare actual results against forecasts, budgets, and prior periods by pulling data from planning systems, financial platforms, and reporting tools. The AI agent standardizes calculations to eliminate inconsistencies in how different departments measure the same metrics.
Performance Measurement
Compare actual results against forecasts, budgets, and prior periods by pulling data from planning systems, financial platforms, and reporting tools. The AI agent standardizes calculations to eliminate inconsistencies in how different departments measure the same metrics.
Multi-source Data Analysis
Connect to CRMs (Salesforce, Hubspot), ERPs (SAP, NetSuite), financial systems (QuickBooks, Xero), databases, spreadsheets, presentations, and web sources. Analyze both structured data from systems and unstructured information from documents and web content.
Multi-source Data Analysis
Connect to CRMs (Salesforce, Hubspot), ERPs (SAP, NetSuite), financial systems (QuickBooks, Xero), databases, spreadsheets, presentations, and web sources. Analyze both structured data from systems and unstructured information from documents and web content.
Multi-source Data Analysis
Connect to CRMs (Salesforce, Hubspot), ERPs (SAP, NetSuite), financial systems (QuickBooks, Xero), databases, spreadsheets, presentations, and web sources. Analyze both structured data from systems and unstructured information from documents and web content.
Cross-platform Metric Tracking
Monitor specific business metrics consistently even when the underlying data spans multiple systems. Create a single source of truth for NPS scores, customer acquisition costs, inventory levels, and operational KPIs regardless of where the source data resides.
Cross-platform Metric Tracking
Monitor specific business metrics consistently even when the underlying data spans multiple systems. Create a single source of truth for NPS scores, customer acquisition costs, inventory levels, and operational KPIs regardless of where the source data resides.
Cross-platform Metric Tracking
Monitor specific business metrics consistently even when the underlying data spans multiple systems. Create a single source of truth for NPS scores, customer acquisition costs, inventory levels, and operational KPIs regardless of where the source data resides.
Integrated Performance Monitoring
Get early warning of issues by analyzing data across departmental boundaries. Identify when marketing metrics, sales performance, and financial indicators show misalignment or concerning patterns that wouldn't be visible when looking at each system separately.
Integrated Performance Monitoring
Get early warning of issues by analyzing data across departmental boundaries. Identify when marketing metrics, sales performance, and financial indicators show misalignment or concerning patterns that wouldn't be visible when looking at each system separately.
Integrated Performance Monitoring
Get early warning of issues by analyzing data across departmental boundaries. Identify when marketing metrics, sales performance, and financial indicators show misalignment or concerning patterns that wouldn't be visible when looking at each system separately.
Why V7 Go
Data sources processed by the AI Business Analytics Agent
Key metrics extracted across platforms
Workflow
Workflow
Import your files
Salesforce
,
SAP
,
Power BI
CRM Systems (Salesforce, Hubspot)
CRM Systems (Salesforce, Hubspot)
CRM Systems (Salesforce, Hubspot)
CRM Systems (Salesforce, Hubspot)
ERP Platforms (SAP, NetSuite)
ERP Platforms (SAP, NetSuite)
ERP Platforms (SAP, NetSuite)
ERP Platforms (SAP, NetSuite)
Financial Software (QuickBooks, Xero)
Financial Software (QuickBooks, Xero)
Financial Software (QuickBooks, Xero)
Financial Software (QuickBooks, Xero)
Business Intelligence Tools (Tableau, Power BI)
Business Intelligence Tools (Tableau, Power BI)
Business Intelligence Tools (Tableau, Power BI)
Business Intelligence Tools (Tableau, Power BI)
Spreadsheets and Presentations
Spreadsheets and Presentations
Spreadsheets and Presentations
Spreadsheets and Presentations
Databases and APIs
Databases and APIs
Databases and APIs
Databases and APIs
Revenue and sales performance
Revenue and sales performance
Revenue and sales performance
Revenue and sales performance
Customer acquisition and retention metrics
Customer acquisition and retention metrics
Customer acquisition and retention metrics
Customer acquisition and retention metrics
Product profitability and margins
Product profitability and margins
Product profitability and margins
Product profitability and margins
Marketing campaign effectiveness
Marketing campaign effectiveness
Marketing campaign effectiveness
Marketing campaign effectiveness
Operational efficiency indicators
Operational efficiency indicators
Operational efficiency indicators
Operational efficiency indicators
Financial health and cash flow metrics
Financial health and cash flow metrics
Financial health and cash flow metrics
Financial health and cash flow metrics
Inventory and supply chain performance
Inventory and supply chain performance
Inventory and supply chain performance
Inventory and supply chain performance
Employee productivity and engagement
Employee productivity and engagement
Employee productivity and engagement
Employee productivity and engagement
Customer satisfaction and feedback data
Customer satisfaction and feedback data
Customer satisfaction and feedback data
Customer satisfaction and feedback data
Market share and competitive positioning
Market share and competitive positioning
Market share and competitive positioning
Market share and competitive positioning
Time comparison
Time comparison
Time comparison
Time comparison
Traditional way
10-15 hours per reporting cycle
10-15 hours per reporting cycle
With V7 Go agents
30-45 minutes per reporting cycle
30-45 minutes per reporting cycle
Average time saved
92-95%
92-95%
V7 Go
V7 Go
V7 Go
V7 Go
AI solutions
AI solutions
for business professionals
Business teams spend 15+ hours weekly piecing together data from disconnected sources—CRMs, ERPs, spreadsheets, presentations, and analytics platforms—creating inconsistent views of performance. Critical insights remain buried in siloed systems, departments use different calculation methods for the same metrics, and decision-makers can't trust the numbers they receive. V7 Go's AI business analytics agent connects to multiple data sources, extracts consistent metrics, identifies meaningful trends, and delivers reliable performance measurement across your entire organization.
Business Intelligence Teams
Connect all your data sources without building and maintaining dozens of custom integrations. Let AI normalize metrics across systems so you can focus on insights instead of data preparation.
Business Intelligence Teams
Connect all your data sources without building and maintaining dozens of custom integrations. Let AI normalize metrics across systems so you can focus on insights instead of data preparation.
Business Intelligence Teams
Connect all your data sources without building and maintaining dozens of custom integrations. Let AI normalize metrics across systems so you can focus on insights instead of data preparation.
Business Intelligence Teams
Connect all your data sources without building and maintaining dozens of custom integrations. Let AI normalize metrics across systems so you can focus on insights instead of data preparation.
Executive Leadership
Get consistent answers regardless of which department or system holds the data. Make decisions with confidence knowing all your metrics are calculated consistently across the organization.
Executive Leadership
Get consistent answers regardless of which department or system holds the data. Make decisions with confidence knowing all your metrics are calculated consistently across the organization.
Executive Leadership
Get consistent answers regardless of which department or system holds the data. Make decisions with confidence knowing all your metrics are calculated consistently across the organization.
Executive Leadership
Get consistent answers regardless of which department or system holds the data. Make decisions with confidence knowing all your metrics are calculated consistently across the organization.
FAQ
FAQ
FAQ
FAQ
Have questions?
Find answers.
How does the AI analytics agent connect to our various business systems?
The AI agent integrates with your data ecosystem through multiple methods: direct API connections to major business platforms (Salesforce, SAP, NetSuite, Hubspot), database connections (SQL, MongoDB, PostgreSQL), pre-built connectors for analytics tools (Tableau, Power BI, Looker), and file access for document repositories. It can pull data from cloud storage services (Google Drive, SharePoint, Box), email systems, and web sources. The agent maintains secure credentials and connection parameters for each system, enabling it to refresh data regularly without manual intervention. Most customers connect their first 3-5 data sources within one week of implementation.
+
How does the AI analytics agent connect to our various business systems?
The AI agent integrates with your data ecosystem through multiple methods: direct API connections to major business platforms (Salesforce, SAP, NetSuite, Hubspot), database connections (SQL, MongoDB, PostgreSQL), pre-built connectors for analytics tools (Tableau, Power BI, Looker), and file access for document repositories. It can pull data from cloud storage services (Google Drive, SharePoint, Box), email systems, and web sources. The agent maintains secure credentials and connection parameters for each system, enabling it to refresh data regularly without manual intervention. Most customers connect their first 3-5 data sources within one week of implementation.
+
How does the AI analytics agent connect to our various business systems?
The AI agent integrates with your data ecosystem through multiple methods: direct API connections to major business platforms (Salesforce, SAP, NetSuite, Hubspot), database connections (SQL, MongoDB, PostgreSQL), pre-built connectors for analytics tools (Tableau, Power BI, Looker), and file access for document repositories. It can pull data from cloud storage services (Google Drive, SharePoint, Box), email systems, and web sources. The agent maintains secure credentials and connection parameters for each system, enabling it to refresh data regularly without manual intervention. Most customers connect their first 3-5 data sources within one week of implementation.
+
How does the AI analytics agent connect to our various business systems?
The AI agent integrates with your data ecosystem through multiple methods: direct API connections to major business platforms (Salesforce, SAP, NetSuite, Hubspot), database connections (SQL, MongoDB, PostgreSQL), pre-built connectors for analytics tools (Tableau, Power BI, Looker), and file access for document repositories. It can pull data from cloud storage services (Google Drive, SharePoint, Box), email systems, and web sources. The agent maintains secure credentials and connection parameters for each system, enabling it to refresh data regularly without manual intervention. Most customers connect their first 3-5 data sources within one week of implementation.
+
Can the AI agent reconcile different definitions of the same metric across our systems?
Yes, the AI agent excels at standardizing metrics that are calculated differently across systems and departments. It recognizes when your CRM defines "qualified lead" differently than your marketing platform, or when Finance calculates customer acquisition cost using different components than the Sales team. The agent creates a consistent calculation framework that maps data elements from each source to produce standardized metrics. This approach eliminates the common problem of executives receiving different answers to the same question depending on which system or department provided the data.
+
Can the AI agent reconcile different definitions of the same metric across our systems?
Yes, the AI agent excels at standardizing metrics that are calculated differently across systems and departments. It recognizes when your CRM defines "qualified lead" differently than your marketing platform, or when Finance calculates customer acquisition cost using different components than the Sales team. The agent creates a consistent calculation framework that maps data elements from each source to produce standardized metrics. This approach eliminates the common problem of executives receiving different answers to the same question depending on which system or department provided the data.
+
Can the AI agent reconcile different definitions of the same metric across our systems?
Yes, the AI agent excels at standardizing metrics that are calculated differently across systems and departments. It recognizes when your CRM defines "qualified lead" differently than your marketing platform, or when Finance calculates customer acquisition cost using different components than the Sales team. The agent creates a consistent calculation framework that maps data elements from each source to produce standardized metrics. This approach eliminates the common problem of executives receiving different answers to the same question depending on which system or department provided the data.
+
Can the AI agent reconcile different definitions of the same metric across our systems?
Yes, the AI agent excels at standardizing metrics that are calculated differently across systems and departments. It recognizes when your CRM defines "qualified lead" differently than your marketing platform, or when Finance calculates customer acquisition cost using different components than the Sales team. The agent creates a consistent calculation framework that maps data elements from each source to produce standardized metrics. This approach eliminates the common problem of executives receiving different answers to the same question depending on which system or department provided the data.
+
How does the AI agent combine structured data from our systems with unstructured information from documents?
The AI agent bridges structured and unstructured data sources through contextual understanding. It can extract quantitative data from CRM fields or database tables while also identifying relevant metrics buried in board presentations, analyst reports, or strategy documents. For example, it might combine actual sales figures from your ERP with growth projections from planning documents and market size estimates from industry reports. This comprehensive approach provides context that's missing when analyzing only structured data, while adding precision that's lacking when reviewing only documents.
+
How does the AI agent combine structured data from our systems with unstructured information from documents?
The AI agent bridges structured and unstructured data sources through contextual understanding. It can extract quantitative data from CRM fields or database tables while also identifying relevant metrics buried in board presentations, analyst reports, or strategy documents. For example, it might combine actual sales figures from your ERP with growth projections from planning documents and market size estimates from industry reports. This comprehensive approach provides context that's missing when analyzing only structured data, while adding precision that's lacking when reviewing only documents.
+
How does the AI agent combine structured data from our systems with unstructured information from documents?
The AI agent bridges structured and unstructured data sources through contextual understanding. It can extract quantitative data from CRM fields or database tables while also identifying relevant metrics buried in board presentations, analyst reports, or strategy documents. For example, it might combine actual sales figures from your ERP with growth projections from planning documents and market size estimates from industry reports. This comprehensive approach provides context that's missing when analyzing only structured data, while adding precision that's lacking when reviewing only documents.
+
How does the AI agent combine structured data from our systems with unstructured information from documents?
The AI agent bridges structured and unstructured data sources through contextual understanding. It can extract quantitative data from CRM fields or database tables while also identifying relevant metrics buried in board presentations, analyst reports, or strategy documents. For example, it might combine actual sales figures from your ERP with growth projections from planning documents and market size estimates from industry reports. This comprehensive approach provides context that's missing when analyzing only structured data, while adding precision that's lacking when reviewing only documents.
+
Can the AI analytics agent push insights back into our business systems?
Yes, the AI agent operates bidirectionally with your business systems. It can not only extract data but also enrich your platforms with the insights it generates. For example, it can flag accounts in your CRM that show churn risk indicators, update your ERP with inventory optimization recommendations, or populate your BI dashboards with trend data and forecasts. This closed-loop capability ensures insights don't remain isolated in reports but actually drive action within your operational systems. The agent's API allows custom integration patterns tailored to your specific workflow requirements.
+
Can the AI analytics agent push insights back into our business systems?
Yes, the AI agent operates bidirectionally with your business systems. It can not only extract data but also enrich your platforms with the insights it generates. For example, it can flag accounts in your CRM that show churn risk indicators, update your ERP with inventory optimization recommendations, or populate your BI dashboards with trend data and forecasts. This closed-loop capability ensures insights don't remain isolated in reports but actually drive action within your operational systems. The agent's API allows custom integration patterns tailored to your specific workflow requirements.
+
Can the AI analytics agent push insights back into our business systems?
Yes, the AI agent operates bidirectionally with your business systems. It can not only extract data but also enrich your platforms with the insights it generates. For example, it can flag accounts in your CRM that show churn risk indicators, update your ERP with inventory optimization recommendations, or populate your BI dashboards with trend data and forecasts. This closed-loop capability ensures insights don't remain isolated in reports but actually drive action within your operational systems. The agent's API allows custom integration patterns tailored to your specific workflow requirements.
+
Can the AI analytics agent push insights back into our business systems?
Yes, the AI agent operates bidirectionally with your business systems. It can not only extract data but also enrich your platforms with the insights it generates. For example, it can flag accounts in your CRM that show churn risk indicators, update your ERP with inventory optimization recommendations, or populate your BI dashboards with trend data and forecasts. This closed-loop capability ensures insights don't remain isolated in reports but actually drive action within your operational systems. The agent's API allows custom integration patterns tailored to your specific workflow requirements.
+
How does the AI agent handle our proprietary internal metrics and calculations?
The AI agent learns your organization's specific metrics, calculations, and terminology through a combination of example-based training and explicit rules. For unique metrics like custom health scores, proprietary profitability calculations, or industry-specific KPIs, you can show the agent where these metrics appear in your systems and documents. The agent creates a knowledge graph of your business language and calculation methods, continuously improving its understanding as it processes more of your data. This customization ensures the agent speaks your business language rather than forcing you to adapt to generic analytics frameworks.
+
How does the AI agent handle our proprietary internal metrics and calculations?
The AI agent learns your organization's specific metrics, calculations, and terminology through a combination of example-based training and explicit rules. For unique metrics like custom health scores, proprietary profitability calculations, or industry-specific KPIs, you can show the agent where these metrics appear in your systems and documents. The agent creates a knowledge graph of your business language and calculation methods, continuously improving its understanding as it processes more of your data. This customization ensures the agent speaks your business language rather than forcing you to adapt to generic analytics frameworks.
+
How does the AI agent handle our proprietary internal metrics and calculations?
The AI agent learns your organization's specific metrics, calculations, and terminology through a combination of example-based training and explicit rules. For unique metrics like custom health scores, proprietary profitability calculations, or industry-specific KPIs, you can show the agent where these metrics appear in your systems and documents. The agent creates a knowledge graph of your business language and calculation methods, continuously improving its understanding as it processes more of your data. This customization ensures the agent speaks your business language rather than forcing you to adapt to generic analytics frameworks.
+
How does the AI agent handle our proprietary internal metrics and calculations?
The AI agent learns your organization's specific metrics, calculations, and terminology through a combination of example-based training and explicit rules. For unique metrics like custom health scores, proprietary profitability calculations, or industry-specific KPIs, you can show the agent where these metrics appear in your systems and documents. The agent creates a knowledge graph of your business language and calculation methods, continuously improving its understanding as it processes more of your data. This customization ensures the agent speaks your business language rather than forcing you to adapt to generic analytics frameworks.
+
How does the AI analytics agent maintain data security when accessing our sensitive business systems?
The AI agent follows enterprise-grade security protocols for all system connections. It uses OAuth, API keys, or other secure authentication methods without storing plaintext credentials. All data transfers are encrypted both in transit and at rest, with SOC 2 Type II and ISO 27001 compliance. Role-based permissions control which metrics and data sources are accessible to different user groups. For highly sensitive financial or customer data, on-premises deployment options keep your information within your security perimeter. The agent maintains detailed access logs for all data source interactions, providing complete audit trails for compliance requirements.
+
How does the AI analytics agent maintain data security when accessing our sensitive business systems?
The AI agent follows enterprise-grade security protocols for all system connections. It uses OAuth, API keys, or other secure authentication methods without storing plaintext credentials. All data transfers are encrypted both in transit and at rest, with SOC 2 Type II and ISO 27001 compliance. Role-based permissions control which metrics and data sources are accessible to different user groups. For highly sensitive financial or customer data, on-premises deployment options keep your information within your security perimeter. The agent maintains detailed access logs for all data source interactions, providing complete audit trails for compliance requirements.
+
How does the AI analytics agent maintain data security when accessing our sensitive business systems?
The AI agent follows enterprise-grade security protocols for all system connections. It uses OAuth, API keys, or other secure authentication methods without storing plaintext credentials. All data transfers are encrypted both in transit and at rest, with SOC 2 Type II and ISO 27001 compliance. Role-based permissions control which metrics and data sources are accessible to different user groups. For highly sensitive financial or customer data, on-premises deployment options keep your information within your security perimeter. The agent maintains detailed access logs for all data source interactions, providing complete audit trails for compliance requirements.
+
How does the AI analytics agent maintain data security when accessing our sensitive business systems?
The AI agent follows enterprise-grade security protocols for all system connections. It uses OAuth, API keys, or other secure authentication methods without storing plaintext credentials. All data transfers are encrypted both in transit and at rest, with SOC 2 Type II and ISO 27001 compliance. Role-based permissions control which metrics and data sources are accessible to different user groups. For highly sensitive financial or customer data, on-premises deployment options keep your information within your security perimeter. The agent maintains detailed access logs for all data source interactions, providing complete audit trails for compliance requirements.
+
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Extract business metrics from reports and presentations. Track KPIs, analyze trends, and monitor performance with consistent measurement.
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Performance Trend ID
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Extract business metrics from reports and presentations. Track KPIs, analyze trends, and monitor performance with consistent measurement.
KPI Tracking
Performance Trend ID
Measurement Standardization
Business
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Extract business metrics from reports and presentations. Track KPIs, analyze trends, and monitor performance with consistent measurement.
KPI Tracking
Performance Trend ID
Measurement Standardization
Next steps
Stop piecing together metrics from disconnected systems and documents
Get consistent business intelligence from all your data sources
You’ll hear back in less than 24 hours
Next steps
Stop piecing together metrics from disconnected systems and documents
Get consistent business intelligence from all your data sources
You’ll hear back in less than 24 hours
Next steps
Stop piecing together metrics from disconnected systems and documents
Get consistent business intelligence from all your data sources
You’ll hear back in less than 24 hours
Next steps
Stop piecing together metrics from disconnected systems and documents
Get consistent business intelligence from all your data sources