MK
Market data
Public market prices, indices, commodities, securities and market-update fields where available.
Finance data intelligence
AI-powered financial market data scraping
Turn relevant public financial, company and news signals into structured datasets for research, monitoring and informed market decisions.
Financial research often depends on information spread across many public sources. We build tailored workflows that collect, normalize and deliver agreed public data fields so analysts can spend less time gathering and more time interpreting.
From public pages to useful data
What is finance data scraping?
Financial research often depends on information spread across many public sources. We build tailored workflows that collect, normalize and deliver agreed public data fields so analysts can spend less time gathering and more time interpreting.
Cigma combines tailored extraction logic with AI-assisted mapping and validation where appropriate. The objective is a dependable dataset that fits your research, commercial or operational workflow—not an unstructured collection of raw pages.
Data we extract
Build the dataset your team actually needs
Every project starts with a field map. We collect only publicly available information that is relevant to your use case, then normalize it into an agreed structure.
CO
Company data
Public company profiles, announcements, filings, events and competitive signals.
NW
News data
Headlines, dates, source details, topics and entity references from selected public news sources.
EV
Event data
Public corporate events, earnings dates, announcements and calendar-facing information.
AL
Alternative data
Public-web indicators selected for a defined research or monitoring workflow.
HS
Historical data
Historical records and normalized fields where public sources and project requirements allow.
From data to decisions
Finance intelligence use cases
The same public data can answer different business questions. We define collection and output around the decisions your team needs to make.
MM
Market monitoring
Collect relevant public market and event signals on an agreed schedule.
CI
Company intelligence
Organize public company updates and competitive information for research workflows.
NR
News research
Track selected public financial and business coverage by topic, entity or source.
TR
Trend analysis
Prepare normalized historical datasets for analysis and reporting.
AD
Alternative data
Broaden research context with agreed public-web indicators.
DL
Data delivery
Feed structured research data into analyst tools, databases or dashboards.
AI-powered extraction
A more structured route from page to dataset
AI can help identify page context, map relevant values to defined fields and validate records against agreed rules. We use it as part of a practical workflow—not as an unsupported promise of fully autonomous collection.
- Understand the source and required field structure
- Extract relevant publicly available information
- Validate, normalize and remove duplicates where required
- Structure records to match your agreed schema
- Deliver data in the format and frequency you need
Public web sources
Custom workflows for the sources you need
We define sources, fields, refresh rates and delivery formats around your research use case. Public availability and source feasibility are assessed before delivery is committed.
We do not claim support for a source until the required workflow has been assessed.
Who uses this data
Useful across specialist teams
- Financial research teams
- Investment and market-analysis firms
- Corporate strategy teams
- Risk and compliance research teams
- Data and analytics platforms
- Consulting and advisory businesses
Flexible delivery
Get data in the format you need
Your delivery method should fit the people and systems using the data. We can prepare structured outputs for one-time or scheduled delivery.
- CSV, Excel, JSON and XML files
- API or database-ready delivery
- Cloud storage and custom data feeds
- One-time datasets or scheduled updates
- Field normalization based on your schema
How Cigma works
A transparent data workflow
01
Define requirements
Share the public sources, fields, geography and update frequency that matter to your team.
02
Design the workflow
We assess source feasibility and configure an extraction and data-structure approach.
03
Extract and validate
Public information is collected, normalized and checked against the agreed data rules.
04
Deliver the dataset
Receive a sample or feed in the agreed format so your team can begin using the information.
05
Monitor and update
For recurring needs, the workflow can be maintained and run on an agreed schedule.
06
Refine as you learn
Add or refine fields as your commercial, research or product questions evolve.
Explore more data intelligence
Related AI-powered web scraping solutions
Explore the AI-powered web scraping service hub or review other industry data solutions: E-commerce, Travel & Tourism, Food Delivery, Entertainment, Jobs & Recruitment, News & Media, Real Estate.
Frequently asked questions
Finance data scraping FAQs
What is financial data scraping?
It is the structured collection of relevant publicly available market, company, news and event information for research workflows.
Can Cigma collect real-time financial data?
Update frequency depends on the source, public availability and project requirements. We agree the appropriate schedule during scoping.
How is financial data delivered?
Data can be prepared for CSV, Excel, JSON, API, database or cloud-storage delivery based on the agreed workflow.
How is data delivered?
We can prepare agreed datasets for CSV, Excel, JSON, XML, API, database or cloud-storage delivery.
Is public web data collection legal?
Each project should be assessed individually. We focus on publicly available information while considering applicable laws, privacy requirements, contractual restrictions and website terms.
How do we get started?
Share the public sources, fields, geography and refresh frequency you need. We will help define a practical scope.