Natural Language Processing

Natural language processing (NLP) is the branch of artificial intelligence that lets software read, understand and produce human language, written or spoken. It turns a request such as “which vans are due for service this month?” into a query and the result back into a sentence. It is the engine behind chatbots, voice assistants and AI agents.

The two halves of NLP

• Natural language understanding (NLU): identifying the intent of a sentence and its key entities, such as a vehicle, a site, a date or a cost category, despite different wordings, typos or ambiguity.
• Natural language generation (NLG): writing a correct, natural answer, a summary or a draft from data.

Modern systems rely on large language models, a type of neural network trained on vast amounts of text. They handle both halves in one model, which explains the recent jump in quality of conversational AI.

How it works in practice

A typical pipeline splits text into tokens, interprets meaning in context, links entities to records in a database, retrieves the relevant facts and generates a response. Reliable business tools add a key safeguard: the answer must be grounded in the company's own data rather than invented by the model. Permissions also matter, so that each user only sees what they are allowed to see. Finally, the system should show where an answer comes from, so that a manager can check the underlying record before acting on it, especially for costs, compliance deadlines or anything sent to drivers.

Uses in transport and fleets

• Questions in plain language: asking for costs, upcoming deadlines or vehicle availability without building a report.
• Document reading: extracting dates, amounts and plate numbers from invoices, contracts or fines.
• Voice in the cab: hands-free navigation and controls through the vehicle's human-machine interface.
• Summaries: turning many alerts into a short list of priorities.

NLP is related to generative AI in transportation, which focuses on producing new content and plans.

How Dadycar helps

Dadycar is a French fleet management software that puts NLP to work through Donna, its AI agent. Fleet managers ask questions in everyday language and Donna answers from the fleet's real records: vehicles, documents, maintenance, costs, fines and telematics data. It suggests actions that are carried out only after approval. Data is hosted in France, with OVHcloud. Dadycar received the innovation award at the Rencontres Flotauto 2025.

FAQ

What is the difference between NLP and conversational AI?
NLP is the underlying language technology; conversational AI is a product built on it to hold a dialogue.

Can NLP make mistakes?
Yes. Language models can misread a request or produce wrong statements, which is why answers should be grounded in verified data.

Does NLP work in several languages?
Modern models handle many languages, so a team can ask questions in the language it uses every day.