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Increase your company's productivity through the automated classification, labeling, display and search of your text documents

We cannot improve what we do not measure. Artificial intelligence applied to text.

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2.5 quintillion bytes of data are created every day

Data in text documents accounts for more than 85% of the business information of companies, while less than 2% are used for company decision-making.

85%

Data in text documents

2%

Business decision-making

Intelligent document classification, search and labeling suite

The objective is to improve document organization and interpretation capabilities.

Automated classification and labeling of documents
Automated classification and labeling of documents

Employ mono-label or multi-label classification of your documents (contracts, emails, bid specifications or other internal documents) and maximize your productivity.

Identification of key data and extraction of information
Identification of key data and extraction of information

Identify key points in documents (people, places, organizations, roles, etc.) to quickly assist decision-making about those documents.

Document similarity search
Document similarity search

Drag your document, copy a paragraph, filter by label, or use our free text search bar to find in seconds the documents needed for your work, while detecting duplicates or documents useless to your business and thus optimizing storage space.

Data display and text analysis
Data display and text analysis

Powerful management dashboard enabling you to combine and filter numerous labels, dates, subjects and other meta-data facilitating in-depth analysis and interpretation of data in text documents.

Success stories Talk

Success stories
Talk

Objective: Leading European company in legal information challenged to improve its customers’ experience.

Outcome:

+95%

Accuracy of the classifiers

<1s

Calculation time of the models developed

+90%

Relevance in the search for similar documents

Contact Foqum and discover what we can do for you

Remember: we cannot improve what we do not measure.

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