Turn unstructured text into value with NLP

Natural language processing enables computers to understand human language. Computers are naturally able to process this data much faster than humans, which means that companies are now turning previously unused data into meaningful information. For instance, information can be automatically extracted from internal reports, service logs or case files and interpreted by computers.

 

Recent innovations in the field of NLP have allowed AI algorithms to understand the context in which words appear. This opens the door for computers to understand spoken and written language. We can already see this when in voice-controlled smart devices such as Amazon Alexa or Apple Siri. It is a remarkable achievement and creates the potential for more powerful search engines and information retrieval systems. It also allows you to add further automation to your administrative processes.

Imagine the revelations of all the massive amounts of unstructured text you gather in your organisation and from your stakeholders. It may hold the key to the best strategy for your organisation ever.
—  Julie Dermumeaux, Team Lead Data Science

Information extraction

Information extraction helps you process large amounts of text and organise unstructured text into categories. It enables you to pull out pre-defined information from text and can helps you to recognise and extract relevant keywords and features (such as product codes, colours and specifications) or named entities (such as the names of people, locations, or company names). 

Our text extraction tools can also enable to you automatically find key terms in legal documents, for instance, or identify the main words in customer support tickets. These tools can also be used in accounting, for classifying invoices or entering recurring invoices. Text extraction also offers a wealth of other possibilities such as tracking news, reports and comments and can be valuable for journalists and financial traders.

 

Summarisation

Machines can consistently and rapidly analyse more language-based data than humans, and do not need to stop for a break.

 

Summarisation allows you to:

 

  • Identify the most relevant information and shorten texts
  • Turn unstructured text into useable data
  • Process all kinds of texts, including social media comments, online reviews and even financial, medical and legal documents

 

New: START AI

The START AI initiative aims to support companies in their intention to explore AI applications by valorising their data.

If your company is eligible, ML2Grow will guide your company for three days to explore the possibilities of AI/data to identify the most relevant applications for your organisation.

Together with our team:

  • Evaluate the value of the available company data (internal & external)
  • Identify if there are relevant AI/data projects within your business context
  • Determine which stakeholders and experts to involve in your potential projects
  • Get tips & tricks with which you can better estimate the added value of your possible AI projects
  • Map the next steps in your AI journey

ML2Grow’s services will cover three days and include preparation, analysis and reporting, and participation in meetings (onsite or remote). These services will be provided over a maximum of 4 months (between the beginning of June and the end of September 2022).

The intervention of ML2Grow could lead to the conclusion that AI applications are not relevant for the participating company. In this case, the guidance will mainly focus on coherent data management to promote potential data projects.

Who can participate?

Any SME (max. 250 employees), organisation or association, starting or established, regardless of its digital maturity or sector.

Costs

The cost for participation is €1625 excl. VAT

This corresponds to 30% of the fair value of the guidance.

Are you interested in participating?

Contact our team before the 15th of May if you are interested in this offer.

We will happily answer all of your questions and support the application procedure.

 

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Document classification

Document classification lets you organise unstructured text into categories. It works by applying tags to documents from a predefined list and simplifies the organisation and maintenance of documents and data.

It is a good way to analyse large amounts of information. For instance, if you have open-ended feedback forms, you can find out how many responses mention your customer support and what percentage of visitors talk about pricing. 

 

Benefits

  • Accelerated workflows at lower costs. Improve the customer experience and throughput rate of your classification-heavy processes without increasing costs.
  • Compliance. Easily and comprehensively scan documents for any type of sensitive information. Once identified, the software can even redact the information.
  • Discovery. Automate the process of grouping documents and use this information to process an entire volume of documents to support legal or compliance needs.
  • Migration. Take collections of documents and easily organize, extract, and apply key metadata to simplify and organize documents into a content management system.
  • Reduce ROT (Redundancy, Obsolete, Trivial). Identify duplicate documents and documents that don’t need to be preserved and easily remove them.
Gilles Deweerdt

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