Documents and language
Natural language processing: let the machine read your documents
Contracts, emails, tickets, meeting notes: much of what an organisation knows is written in everyday language. Natural language processing makes it usable, in English and in French.
What natural language processing is
Natural language processing (NLP) covers the techniques that let a program read, classify, summarise or write text. Recent language models are part of this field: they understand a question asked in ordinary words and answer it from the documents they are given.
The benefit for an organisation is easy to state. As long as a person has to open every document to find out what is in it, volume is a bottleneck. Once the machine does that first reading, your teams can concentrate on the cases that need their judgement.
What language processing makes possible
Typical examples of what the service makes possible.
Sort incoming requests
Recognise what an email or ticket is about and route it to the right team, with the useful details already extracted.
Extract data from your documents
Pick out amounts, dates, references or clauses from a batch of documents automatically, then feed them into your system.
Query your own content
An internal assistant answers staff questions from your procedures, contracts or document stores.
Find the themes in a large volume of text
Bring out the recurring subjects in conversations, survey responses or comments.
What we deliver
- Document extraction and classification, tuned on your own examples
- An internal assistant that draws on your content
- English and French handled by design
- Data handling documented for your GDPR register
Who this service is for
- Your teams spend time reading, sorting or re-keying text.
- Volume is growing faster than your capacity to handle it.
- The information exists, but nobody can find it when it is needed.
Where no error can be tolerated and no human review is possible, the use case calls for other safeguards. We discuss them during discovery.
How it works
We start from a sample of your real documents rather than demonstration examples. Discovery narrows the work to one type of document or request; the proof of value measures the result on that scope, against the number you chose. Integration then connects the processing to your tools, with security and data handling documented. The decision is yours after each step.
Frequently asked questions about AI as a Service
Can an internal assistant get things wrong?
Yes. A language model can give a wrong answer with complete confidence. The risk is reduced by having it answer from your own content, showing the passages it used, and leaving the final decision to a person wherever a mistake would be costly.
What kinds of content can be processed?
Documents, emails, tickets, conversations: any digital text.
Is French handled as well as English?
Both languages are planned for from the design stage. The vocabulary of your own trade matters as much as the language, though, which is why the proof of value is run on your documents.
More documents than your teams can read?
Tell us what the texts are and what you would like to get out of them. We reply within one working day.
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