We are a Big DataFinancial Engineering and News Analytics company. Our cutting edge algorithms transform unstructured data for financial assets or business topics into time series. We help visualize in an insightful way to reduce time for analysis.

Coming soon on Bloomberg FinSentS Web Application


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data:image/jpeg;base64,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
  • FinSentS V2

    Financial News and Sentiment Screener

  • Trading Technology

    Low Latency Trading Technology

  • Sentiment Market Data

    Download our Market Data through our API or our data vendors partners. Real time / Low Latency / up to 15 years of history on > 40k quoted or unquoted stocks, oil & gas, major commodities, currencies, real estate... We can help you generating αlpha!

  • Big Data

    How can you track the humongous amount of information produced everyday? In News, Blogs, Social Media, Proprietary dataset? Is it just noise?

Solutions | Data Providersnews agencies, online brokers, vendors ...

  • Provide news analytics to your customers
  • Sentiment APIs
  • White labeling of our semantic engine

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Solutions | Tradingtraders, asset managers, brokers, hedge funds, and more

News sentiment for Equity, FX, Commodities
Feed your trading algorithms
Sentiment technical indicators

 

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Solutions | Consulting Comp.business or specialised press

  • Competitive intelligence
  • Up to date information for your staffs and clients
  • Tailor-made solution

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Solutions | Risk and Compliancemarket, credit risk, compliance

  • Comply with regulation
  • Track abnormality in volume/sentiment
  • Real-time alerts and triggers

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Products | Sentiment Indexesstandard or custom

  • Country or Political index
  • Replicate any equity or market index
  • Up to 5 years of history

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Services | Bespokeon demand development

  • Ad hoc and custom development
  • Financial or Semantic Engineering
  • Contact us for more details ...

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