AI Multi-Document Correlation Agent
Connect the dots. Find the alpha.
Connect the dots. Find the alpha.
Delegate your deepest research to a specialized AI agent. It reads across your entire document universe—contracts, financials, reports, emails—to find the subtle correlations, patterns, and contradictions that lead to breakthrough insights and a true information advantage.
Why V7 Go
Why V7 Go
Pattern & Trend Detection
Analyzes data across thousands of documents to identify recurring themes, patterns, and trends that would be impossible for a human to spot, such as a specific contract clause that consistently leads to disputes.
Pattern & Trend Detection
Analyzes data across thousands of documents to identify recurring themes, patterns, and trends that would be impossible for a human to spot, such as a specific contract clause that consistently leads to disputes.
Pattern & Trend Detection
Analyzes data across thousands of documents to identify recurring themes, patterns, and trends that would be impossible for a human to spot, such as a specific contract clause that consistently leads to disputes.
Contradiction & Inconsistency Flagging
Acts as an automated auditor, cross-referencing information between multiple sources to find and flag contradictions, such as a discrepancy between a company's marketing claims and its SEC filings.
Contradiction & Inconsistency Flagging
Acts as an automated auditor, cross-referencing information between multiple sources to find and flag contradictions, such as a discrepancy between a company's marketing claims and its SEC filings.
Contradiction & Inconsistency Flagging
Acts as an automated auditor, cross-referencing information between multiple sources to find and flag contradictions, such as a discrepancy between a company's marketing claims and its SEC filings.
Relationship & Network Mapping
Identifies and maps the relationships between entities mentioned across your documents, helping you visualize connections between people, companies, and projects.
Relationship & Network Mapping
Identifies and maps the relationships between entities mentioned across your documents, helping you visualize connections between people, companies, and projects.
Relationship & Network Mapping
Identifies and maps the relationships between entities mentioned across your documents, helping you visualize connections between people, companies, and projects.
Causal Inference Analysis
Surfaces potential cause-and-effect relationships by finding correlations between events and outcomes across your datasets, such as a new product launch and a subsequent spike in support tickets.
Causal Inference Analysis
Surfaces potential cause-and-effect relationships by finding correlations between events and outcomes across your datasets, such as a new product launch and a subsequent spike in support tickets.
Causal Inference Analysis
Surfaces potential cause-and-effect relationships by finding correlations between events and outcomes across your datasets, such as a new product launch and a subsequent spike in support tickets.
Builds on Your Knowledge Hub
Connects your document set to a V7 Go Knowledge Hub of past research, allowing the agent to find correlations not just within the current project, but across your firm's entire history.
Builds on Your Knowledge Hub
Connects your document set to a V7 Go Knowledge Hub of past research, allowing the agent to find correlations not just within the current project, but across your firm's entire history.
Builds on Your Knowledge Hub
Connects your document set to a V7 Go Knowledge Hub of past research, allowing the agent to find correlations not just within the current project, but across your firm's entire history.
Cited and Explainable Insights
This is not a black box. Every identified correlation or pattern is supported by visual citations that link directly to the specific pieces of evidence in the source documents.
Cited and Explainable Insights
This is not a black box. Every identified correlation or pattern is supported by visual citations that link directly to the specific pieces of evidence in the source documents.
Cited and Explainable Insights
This is not a black box. Every identified correlation or pattern is supported by visual citations that link directly to the specific pieces of evidence in the source documents.
Why V7 Go
Reads across your entire dataset
To find the connections and contradictions that matter.
Workflow
Workflow
Import your files
SharePoint
,
Snowflake
,
Databricks
Time comparison
Time comparison
Time comparison
Time comparison
Traditional way
Often Impossible Manually
Often Impossible Manually
With V7 Go agents
Hours
Hours
Average time saved
95%
95%
V7 Go
V7 Go
V7 Go
V7 Go
For the insights you can only find
by reading everything at once
The most powerful insights are often hidden in the connections between documents, but finding them requires a massive manual effort. Analysts are great at going deep on a single document, but no human can read thousands of files simultaneously to find the subtle patterns, contradictions, and correlations that exist across an entire data room or research library. This means your team is constantly at risk of missing the 'aha!' moment that only emerges when all the pieces are put together. How much faster would your business grow if AI could connect the dots for you?
Investment & Diligence Teams
Find the deal-killing red flags that hide in the contradictions between documents. Let an AI agent act as your tireless auditor, cross-referencing every claim in a CIM against the facts in the data room.
Investment & Diligence Teams
Find the deal-killing red flags that hide in the contradictions between documents. Let an AI agent act as your tireless auditor, cross-referencing every claim in a CIM against the facts in the data room.
Investment & Diligence Teams
Find the deal-killing red flags that hide in the contradictions between documents. Let an AI agent act as your tireless auditor, cross-referencing every claim in a CIM against the facts in the data room.
Investment & Diligence Teams
Find the deal-killing red flags that hide in the contradictions between documents. Let an AI agent act as your tireless auditor, cross-referencing every claim in a CIM against the facts in the data room.
Researchers & Intelligence Analysts
Accelerate discovery and find breakthrough insights. Use the agent to analyze vast libraries of research papers, reports, or historical data to find the novel patterns and connections that drive innovation.
Researchers & Intelligence Analysts
Accelerate discovery and find breakthrough insights. Use the agent to analyze vast libraries of research papers, reports, or historical data to find the novel patterns and connections that drive innovation.
Researchers & Intelligence Analysts
Accelerate discovery and find breakthrough insights. Use the agent to analyze vast libraries of research papers, reports, or historical data to find the novel patterns and connections that drive innovation.
Researchers & Intelligence Analysts
Accelerate discovery and find breakthrough insights. Use the agent to analyze vast libraries of research papers, reports, or historical data to find the novel patterns and connections that drive innovation.
More automations
Other automations
Transform your business
with other AI Agents
More agents
More agents
Business
AI RFI Response Generation Agent
Accelerate your sales cycle by automating RFI responses. This V7 Go agent uses your internal knowledge base to instantly draft accurate answers to prospect questionnaires.
RFI Automation
Automated Response Generation
Sales Cycle Acceleration
Business
AI RFI Response Generation Agent
Accelerate your sales cycle by automating RFI responses. This V7 Go agent uses your internal knowledge base to instantly draft accurate answers to prospect questionnaires.
RFI Automation
Automated Response Generation
Sales Cycle Acceleration
Business
AI RFI Response Generation Agent
Accelerate your sales cycle by automating RFI responses. This V7 Go agent uses your internal knowledge base to instantly draft accurate answers to prospect questionnaires.
RFI Automation
Automated Response Generation
Sales Cycle Acceleration
Business
AI RFI Response Generation Agent
Accelerate your sales cycle by automating RFI responses. This V7 Go agent uses your internal knowledge base to instantly draft accurate answers to prospect questionnaires.
RFI Automation
Automated Response Generation
Sales Cycle Acceleration
Business
AI Risk Report Analysis Agent
Automate the analysis and consolidation of all your internal risk reports. This V7 Go agent reads audit, compliance, and incident reports to create a unified risk summary.
Risk Report Consolidation
Automated Risk Summarization
Enterprise Risk Management
Business
AI Risk Report Analysis Agent
Automate the analysis and consolidation of all your internal risk reports. This V7 Go agent reads audit, compliance, and incident reports to create a unified risk summary.
Risk Report Consolidation
Automated Risk Summarization
Enterprise Risk Management
Business
AI Risk Report Analysis Agent
Automate the analysis and consolidation of all your internal risk reports. This V7 Go agent reads audit, compliance, and incident reports to create a unified risk summary.
Risk Report Consolidation
Automated Risk Summarization
Enterprise Risk Management
Business
AI Risk Report Analysis Agent
Automate the analysis and consolidation of all your internal risk reports. This V7 Go agent reads audit, compliance, and incident reports to create a unified risk summary.
Risk Report Consolidation
Automated Risk Summarization
Enterprise Risk Management
Welcome Go
Welcome Go
Welcome Go
Welcome Go
Connect the dots. Find the alpha.
Connect the dots. Find the alpha.
Connect the dots. Find the alpha.
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:
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:
FAQ
FAQ
FAQ
FAQ
Have questions?
Find answers.
How does it 'correlate' information from different documents?
It uses a combination of entity recognition and semantic understanding. It first identifies key entities (like company names, people, or products) and then analyzes the context around those entities in every document to find relationships and contradictions.
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How does it 'correlate' information from different documents?
It uses a combination of entity recognition and semantic understanding. It first identifies key entities (like company names, people, or products) and then analyzes the context around those entities in every document to find relationships and contradictions.
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How does it 'correlate' information from different documents?
It uses a combination of entity recognition and semantic understanding. It first identifies key entities (like company names, people, or products) and then analyzes the context around those entities in every document to find relationships and contradictions.
+
How does it 'correlate' information from different documents?
It uses a combination of entity recognition and semantic understanding. It first identifies key entities (like company names, people, or products) and then analyzes the context around those entities in every document to find relationships and contradictions.
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Can it work on a mix of structured and unstructured data?
Yes, this is its primary strength. It is designed to find the connections between a number in a spreadsheet, a clause in a legal contract, and a statement in an unstructured email thread to form a single, cohesive insight.
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Can it work on a mix of structured and unstructured data?
Yes, this is its primary strength. It is designed to find the connections between a number in a spreadsheet, a clause in a legal contract, and a statement in an unstructured email thread to form a single, cohesive insight.
+
Can it work on a mix of structured and unstructured data?
Yes, this is its primary strength. It is designed to find the connections between a number in a spreadsheet, a clause in a legal contract, and a statement in an unstructured email thread to form a single, cohesive insight.
+
Can it work on a mix of structured and unstructured data?
Yes, this is its primary strength. It is designed to find the connections between a number in a spreadsheet, a clause in a legal contract, and a statement in an unstructured email thread to form a single, cohesive insight.
+
Do we need to tell it what to look for?
You can do both. You can give it a specific query (e.g., 'Compare revenue in document A vs. document B'), or you can use it for unsupervised discovery, asking it to find 'any interesting patterns or contradictions' in a dataset.
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Do we need to tell it what to look for?
You can do both. You can give it a specific query (e.g., 'Compare revenue in document A vs. document B'), or you can use it for unsupervised discovery, asking it to find 'any interesting patterns or contradictions' in a dataset.
+
Do we need to tell it what to look for?
You can do both. You can give it a specific query (e.g., 'Compare revenue in document A vs. document B'), or you can use it for unsupervised discovery, asking it to find 'any interesting patterns or contradictions' in a dataset.
+
Do we need to tell it what to look for?
You can do both. You can give it a specific query (e.g., 'Compare revenue in document A vs. document B'), or you can use it for unsupervised discovery, asking it to find 'any interesting patterns or contradictions' in a dataset.
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What kind of datasets is this best suited for?
It is most powerful on large, complex, and heterogeneous datasets where human analysis is impractical. Prime examples include M&A data rooms, e-discovery productions, scientific research libraries, and historical archives.
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What kind of datasets is this best suited for?
It is most powerful on large, complex, and heterogeneous datasets where human analysis is impractical. Prime examples include M&A data rooms, e-discovery productions, scientific research libraries, and historical archives.
+
What kind of datasets is this best suited for?
It is most powerful on large, complex, and heterogeneous datasets where human analysis is impractical. Prime examples include M&A data rooms, e-discovery productions, scientific research libraries, and historical archives.
+
What kind of datasets is this best suited for?
It is most powerful on large, complex, and heterogeneous datasets where human analysis is impractical. Prime examples include M&A data rooms, e-discovery productions, scientific research libraries, and historical archives.
+
What does the final output look like?
The agent delivers a dynamic report that outlines the key findings, patterns, and contradictions. Each finding is presented as a clear statement, supported by the specific, cited evidence from the source documents.
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What does the final output look like?
The agent delivers a dynamic report that outlines the key findings, patterns, and contradictions. Each finding is presented as a clear statement, supported by the specific, cited evidence from the source documents.
+
What does the final output look like?
The agent delivers a dynamic report that outlines the key findings, patterns, and contradictions. Each finding is presented as a clear statement, supported by the specific, cited evidence from the source documents.
+
What does the final output look like?
The agent delivers a dynamic report that outlines the key findings, patterns, and contradictions. Each finding is presented as a clear statement, supported by the specific, cited evidence from the source documents.
+
How do we know the correlations are meaningful and not just random?
The agent presents the data and the correlation; the human analyst provides the final judgment. By providing full transparency and citations for every finding, the agent empowers your experts to quickly validate whether a correlation is a meaningful insight or just noise.
+
How do we know the correlations are meaningful and not just random?
The agent presents the data and the correlation; the human analyst provides the final judgment. By providing full transparency and citations for every finding, the agent empowers your experts to quickly validate whether a correlation is a meaningful insight or just noise.
+
How do we know the correlations are meaningful and not just random?
The agent presents the data and the correlation; the human analyst provides the final judgment. By providing full transparency and citations for every finding, the agent empowers your experts to quickly validate whether a correlation is a meaningful insight or just noise.
+
How do we know the correlations are meaningful and not just random?
The agent presents the data and the correlation; the human analyst provides the final judgment. By providing full transparency and citations for every finding, the agent empowers your experts to quickly validate whether a correlation is a meaningful insight or just noise.
+