Extract and Structure Insights
from Your Own Content

Using OCR, Machine Learning, and
Natural Language Understanding

In 50+ languages for Typed or Handwritten Text

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Unlock the Value in Your Text Data

Reports, emails, handwritten notes, articles, and all of your textual data has value. Our algorithms can identify,
highlight, parse, and analyse it at scale and at economical prices.

TRUSTED BY

Financial Institutions and Fintech Companies

Extract data from any body of text

Named entity recognition (NER) extracts key points from your text, powered by OCR and a state-of-the-art (SOTA), proprietarily-trained NLU model.

Forms
Letters
Agreements
Email
Reports
Customer Feedback

Many Formats - One Structured Result

Process forms from different departments in different styles and receive a singular, cross-departmental view of the data.

OCR makes handwritten and scanned text machine-readable

Your input data can be strings of text or images of text. We’ll convert it to a machine-readable format for further analysis and munging

Unstructured to structured content

Whether your content is structured or not, our powerful algorithms and data science team can provide you machine-readable, structured output.

Index, Analyse, Summarise

Structure, categorise, sort by sentiment, and paraphrase your content. Generate automated summaries to understand large bodies of text quickly.   

Leverage the power of NLU and Deep Learning

Our financial and linguistic analysts train our models to enhance accuracy for the business and financial world. No more mishaps from basic solutions that fail to adequately understand the nuances of business language. Available in 30+ languages!

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PRocess in 23 languages - No translation needed!

Don't waste money on translating first. Our language-agnostic multilingual model perform analysis in the original language to retain nuance.

English

German

Chinese

French

Spanish

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Choose your privacy level

Over the Web

Over our API via HTTPS

Secure Cloud

Our models on your cloud servers

On-site

For utmost privacy, use our models on our own internal servers, physically on site.

About CityFALCON:

  • We are a dynamic team of 40 across offices in 3 countries (London, Malta, Ukraine). 
  • Founded in 2014 to understand the natural language data of the financial markets, we’ve grown into a Big Data company built on an extensive pipeline that brings analytics and insights to users.
  • Our 6 years of data science, automation, and scaling for Big Data provides the basis to bring affordable solutions to clients on the NLU and processing aspects of their business.
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