90% less data prep time
AI Market Data Integration Agent
From fragmented sources to unified intelligence
Stop manually aggregating market data from disparate sources. This specialized agent connects to your data feeds, normalizes inconsistent formats, reconciles conflicting values, and delivers a single source of truth—ready for analysis, modeling, and decision-making.

Ideal for
Investment Research
Quantitative Analysis
Portfolio Management

See AI Market Data Integration Agent in action
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See AI Market Data Integration Agent in action
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See AI Market Data Integration Agent in action
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Q3 Market Data Pipeline
See AI Market Data Integration Agent in action
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Time comparison
Time comparison
Traditional way
6-8 hours per week
With V7 Go agents
30-45 minutes
Average time saved
90%
Why V7 Go
Why V7 Go
Multi-Source Data Aggregation
Connects to Bloomberg, Reuters, SEC filings, proprietary feeds, and custom data sources simultaneously. Pulls all relevant market data in a single operation, eliminating manual copy-paste workflows.
Multi-Source Data Aggregation
Connects to Bloomberg, Reuters, SEC filings, proprietary feeds, and custom data sources simultaneously. Pulls all relevant market data in a single operation, eliminating manual copy-paste workflows.
Multi-Source Data Aggregation
Connects to Bloomberg, Reuters, SEC filings, proprietary feeds, and custom data sources simultaneously. Pulls all relevant market data in a single operation, eliminating manual copy-paste workflows.
Multi-Source Data Aggregation
Connects to Bloomberg, Reuters, SEC filings, proprietary feeds, and custom data sources simultaneously. Pulls all relevant market data in a single operation, eliminating manual copy-paste workflows.
Intelligent Format Normalization
Automatically detects and converts disparate data formats—CSV, JSON, XML, Excel, API responses—into a unified schema. Handles unit conversions, date standardization, and currency normalization without manual intervention.
Intelligent Format Normalization
Automatically detects and converts disparate data formats—CSV, JSON, XML, Excel, API responses—into a unified schema. Handles unit conversions, date standardization, and currency normalization without manual intervention.
Intelligent Format Normalization
Automatically detects and converts disparate data formats—CSV, JSON, XML, Excel, API responses—into a unified schema. Handles unit conversions, date standardization, and currency normalization without manual intervention.
Intelligent Format Normalization
Automatically detects and converts disparate data formats—CSV, JSON, XML, Excel, API responses—into a unified schema. Handles unit conversions, date standardization, and currency normalization without manual intervention.
Conflict Resolution & Reconciliation
When the same data point appears in multiple sources with different values, the agent identifies the discrepancy, applies your reconciliation rules, and flags outliers for review.
Conflict Resolution & Reconciliation
When the same data point appears in multiple sources with different values, the agent identifies the discrepancy, applies your reconciliation rules, and flags outliers for review.
Conflict Resolution & Reconciliation
When the same data point appears in multiple sources with different values, the agent identifies the discrepancy, applies your reconciliation rules, and flags outliers for review.
Conflict Resolution & Reconciliation
When the same data point appears in multiple sources with different values, the agent identifies the discrepancy, applies your reconciliation rules, and flags outliers for review.
Real-Time Data Freshness Monitoring
Tracks update timestamps across all sources and alerts you when data becomes stale. Ensures your analysis is always based on the most current information available.
Real-Time Data Freshness Monitoring
Tracks update timestamps across all sources and alerts you when data becomes stale. Ensures your analysis is always based on the most current information available.
Real-Time Data Freshness Monitoring
Tracks update timestamps across all sources and alerts you when data becomes stale. Ensures your analysis is always based on the most current information available.
Real-Time Data Freshness Monitoring
Tracks update timestamps across all sources and alerts you when data becomes stale. Ensures your analysis is always based on the most current information available.
Structured Output for Immediate Use
Delivers aggregated data in your preferred format—Excel, CSV, JSON, or direct database ingestion. Ready to feed into models, dashboards, and analysis tools without additional transformation.
Structured Output for Immediate Use
Delivers aggregated data in your preferred format—Excel, CSV, JSON, or direct database ingestion. Ready to feed into models, dashboards, and analysis tools without additional transformation.
Structured Output for Immediate Use
Delivers aggregated data in your preferred format—Excel, CSV, JSON, or direct database ingestion. Ready to feed into models, dashboards, and analysis tools without additional transformation.
Structured Output for Immediate Use
Delivers aggregated data in your preferred format—Excel, CSV, JSON, or direct database ingestion. Ready to feed into models, dashboards, and analysis tools without additional transformation.
Audit Trail & Data Lineage
Every data point is tagged with its source, timestamp, and any transformations applied. Complete transparency into where your numbers came from and how they were processed.
Audit Trail & Data Lineage
Every data point is tagged with its source, timestamp, and any transformations applied. Complete transparency into where your numbers came from and how they were processed.
Audit Trail & Data Lineage
Every data point is tagged with its source, timestamp, and any transformations applied. Complete transparency into where your numbers came from and how they were processed.
Audit Trail & Data Lineage
Every data point is tagged with its source, timestamp, and any transformations applied. Complete transparency into where your numbers came from and how they were processed.
Aggregates data from any source
And delivers unified, analysis-ready datasets.
Get started
Get started
Import your files
Snowflake
,
Google Cloud
,
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
Unify your market intelligence.
Unify your market intelligence.
Stop wasting time on data plumbing.
Stop wasting time on data plumbing.
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Finance
•
Legal
•
Insurance
•
Tax
•
Real Estate
Customer Voices
Industrial equipment sales
Read the full story
Industrial equipment sales
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
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 any data format.
From any source.
Market data arrives in countless formats from countless sources. This agent handles CSV, JSON, XML, Excel, API responses, and proprietary formats. It normalizes everything into your preferred schema without requiring manual configuration for each new source.
Input types
CSV & Excel
JSON & XML
API Responses
Custom Formats
Document types
Spreadsheets
APIs
Databases
Web Feeds
Text Files
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Supporting any data format.
From any source.
Market data arrives in countless formats from countless sources. This agent handles CSV, JSON, XML, Excel, API responses, and proprietary formats. It normalizes everything into your preferred schema without requiring manual configuration for each new source.
Input types
CSV & Excel
JSON & XML
API Responses
Custom Formats
Document types
Spreadsheets
APIs
Databases
Web Feeds
Text Files
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Supporting any data format.
From any source.
Market data arrives in countless formats from countless sources. This agent handles CSV, JSON, XML, Excel, API responses, and proprietary formats. It normalizes everything into your preferred schema without requiring manual configuration for each new source.
Input types
CSV & Excel
JSON & XML
API Responses
Custom Formats
Document types
Spreadsheets
APIs
Databases
Web Feeds
Text Files
Vendor_US.xlsx

3
Supply_2023.pptx

Review_Legal.pdf

Deterministic transformations
ensure perfect consistency.
Data normalization isn't guesswork—it's rule-based transformation. The agent applies your reconciliation logic consistently across millions of data points. Every conversion is auditable and reproducible, eliminating the data quality issues that plague manual aggregation.
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)
Deterministic transformations
ensure perfect consistency.
Data normalization isn't guesswork—it's rule-based transformation. The agent applies your reconciliation logic consistently across millions of data points. Every conversion is auditable and reproducible, eliminating the data quality issues that plague manual aggregation.
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)
Deterministic transformations
ensure perfect consistency.
Data normalization isn't guesswork—it's rule-based transformation. The agent applies your reconciliation logic consistently across millions of data points. Every conversion is auditable and reproducible, eliminating the data quality issues that plague manual aggregation.
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)
Complete data lineage
for every data point.
Know exactly where every number came from. The agent tags each data point with its source, timestamp, and transformation history. When a number doesn't match expectations, you can trace it back to its origin instantly.

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
Complete data lineage
for every data point.
Know exactly where every number came from. The agent tags each data point with its source, timestamp, and transformation history. When a number doesn't match expectations, you can trace it back to its origin instantly.

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
Complete data lineage
for every data point.
Know exactly where every number came from. The agent tags each data point with its source, timestamp, and transformation history. When a number doesn't match expectations, you can trace it back to its origin instantly.

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 sensitive market data.
Market data is proprietary and sensitive. V7 Go processes all data within your secure environment, integrating with your existing data governance policies. Data is never shared or used for external purposes.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise-grade security
for sensitive market data.
Market data is proprietary and sensitive. V7 Go processes all data within your secure environment, integrating with your existing data governance policies. Data is never shared or used for external purposes.
Certifications
GDPR
SOC2
HIPAA
ISO
Safety
Custom storage
Data governance
Access-level permissions
Enterprise-grade security
for sensitive market data.
Market data is proprietary and sensitive. V7 Go processes all data within your secure environment, integrating with your existing data governance policies. Data is never shared or used for external purposes.
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 Market Data Integration Agent
Which data sources can the agent connect to?
The agent supports major financial data providers like Bloomberg, Reuters, Yahoo Finance, and SEC Edgar, as well as custom APIs, databases, and file uploads. If you have a specific data source, we can configure a connector for it.
+
Which data sources can the agent connect to?
The agent supports major financial data providers like Bloomberg, Reuters, Yahoo Finance, and SEC Edgar, as well as custom APIs, databases, and file uploads. If you have a specific data source, we can configure a connector for it.
+
Which data sources can the agent connect to?
The agent supports major financial data providers like Bloomberg, Reuters, Yahoo Finance, and SEC Edgar, as well as custom APIs, databases, and file uploads. If you have a specific data source, we can configure a connector for it.
+
How does it handle conflicting data from different sources?
You define reconciliation rules based on your firm's methodology—whether that's using the most recent data, averaging values, or applying a weighted hierarchy. The agent applies these rules consistently and flags any unresolved conflicts for manual review.
+
How does it handle conflicting data from different sources?
You define reconciliation rules based on your firm's methodology—whether that's using the most recent data, averaging values, or applying a weighted hierarchy. The agent applies these rules consistently and flags any unresolved conflicts for manual review.
+
How does it handle conflicting data from different sources?
You define reconciliation rules based on your firm's methodology—whether that's using the most recent data, averaging values, or applying a weighted hierarchy. The agent applies these rules consistently and flags any unresolved conflicts for manual review.
+
Can it work with real-time data feeds?
Yes. The agent can be scheduled to run continuously or on-demand, pulling the latest data from your feeds and updating your aggregated dataset. It's ideal for intraday trading, portfolio monitoring, and live market analysis.
+
Can it work with real-time data feeds?
Yes. The agent can be scheduled to run continuously or on-demand, pulling the latest data from your feeds and updating your aggregated dataset. It's ideal for intraday trading, portfolio monitoring, and live market analysis.
+
Can it work with real-time data feeds?
Yes. The agent can be scheduled to run continuously or on-demand, pulling the latest data from your feeds and updating your aggregated dataset. It's ideal for intraday trading, portfolio monitoring, and live market analysis.
+
What happens if a data source goes down or becomes unavailable?
The agent detects missing sources and alerts you immediately. You can configure fallback sources or use the last known good data while the primary source is restored. No silent failures.
+
What happens if a data source goes down or becomes unavailable?
The agent detects missing sources and alerts you immediately. You can configure fallback sources or use the last known good data while the primary source is restored. No silent failures.
+
What happens if a data source goes down or becomes unavailable?
The agent detects missing sources and alerts you immediately. You can configure fallback sources or use the last known good data while the primary source is restored. No silent failures.
+
How accurate is the data normalization?
The agent uses deterministic transformation rules you define, so accuracy is 100% for format conversion. For reconciliation of conflicting values, accuracy depends on your rules—the agent applies them consistently and flags edge cases for review.
+
How accurate is the data normalization?
The agent uses deterministic transformation rules you define, so accuracy is 100% for format conversion. For reconciliation of conflicting values, accuracy depends on your rules—the agent applies them consistently and flags edge cases for review.
+
How accurate is the data normalization?
The agent uses deterministic transformation rules you define, so accuracy is 100% for format conversion. For reconciliation of conflicting values, accuracy depends on your rules—the agent applies them consistently and flags edge cases for review.
+
Can we integrate this with our existing data warehouse?
Absolutely. The agent can write directly to your data warehouse, update your BI tools, or export to your preferred format. It integrates seamlessly with Snowflake, BigQuery, Redshift, and standard databases.
+
Can we integrate this with our existing data warehouse?
Absolutely. The agent can write directly to your data warehouse, update your BI tools, or export to your preferred format. It integrates seamlessly with Snowflake, BigQuery, Redshift, and standard databases.
+
Can we integrate this with our existing data warehouse?
Absolutely. The agent can write directly to your data warehouse, update your BI tools, or export to your preferred format. It integrates seamlessly with Snowflake, BigQuery, Redshift, and standard databases.
+
Next steps
Next steps
Still manually aggregating market data from multiple sources?
Send us your data sources and we'll show you how to unify them into a single, analysis-ready dataset in minutes.
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: