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Data & AI glossaryThe words of data and AI, explained.

Twenty-three terms, each with a short definition and what it means for you.

A

  • AI agent

    A program that relies on an AI model to carry out a multi-step task in your tools: read a request, look up information, write, then hand over to a person for validation.

  • API

    An entry point that lets two software tools exchange data automatically. It is what removes exports, copy-paste and re-entry.

    AutomationDataSee: Data & documents
  • Automation

    Having a machine run a sequence that comes up often: quotes, reminders, updates between software. With or without AI.

C

  • CRM

    The software that tracks your customers and prospects: contacts, conversations, opportunities. A valuable data source, often under-used.

D

  • Dashboard

    A page that brings your indicators together, updated automatically, so you can decide without rebuilding the numbers at every meeting.

  • Data governance

    Who is responsible for which data, which definition is the reference, who has access. Without it, every department keeps its own version of the numbers.

    Governance and securityDataSee: Audit & consulting
  • Data sovereignty

    Keeping control over where your data is stored and processed, and which law applies to it. In practice: hosting in France or Europe, and chosen providers.

    Governance and securityDataSee: Technology

E

  • ERP

    The management software that holds your orders, stock, invoices and purchasing. The heart of your activity figures.

  • ETL

    Extracting data from your software, transforming it (cleaning, harmonising), then loading it into a single source. It is what makes a dashboard reliable.

    DataAutomationSee: Data & documents

F

  • Forecasting model

    A calculation based on your history to estimate what will happen: sales, workload, stock. With 6 to 12 months of data, results are often already useful.

G

  • GDPR

    The European regulation on personal data. It sets what can be collected, why, for how long, and the rights of the people concerned.

    Governance and securitySee: Audit & consulting
  • Generative AI

    Models able to produce text, images or code from an instruction. Useful for writing, summarising, classifying or answering.

H

  • Hallucination

    A wrong answer given confidently by an AI model. It is limited by having the AI answer from your documents and keeping a human validation step.

    AIGovernance and securitySee: Custom apps & websites

K

  • KPI (key indicator)

    A number tracked over time to steer the business: margin, delivery time, conversion rate. Few of them, agreed together, or they are useless.

L

  • LLM (large language model)

    The AI model that understands and writes text, behind assistants such as ChatGPT, Claude or Mistral. It can run with a provider or on your own infrastructure.

M

  • MCP

    A standard that lets an AI assistant connect to your tools (email, CRM, files) in a controlled way, so it can act and not just answer.

N

O

  • OCR

    Automatic reading of the text in a scanned or photographed document, to pick out the useful information.

P

  • Prototype

    A first version running on your real data, built in a few days, so you decide whether to go further on facts rather than slides.

    AIGovernance and securitySee: Audit & consulting

R

  • RAG

    A way of having an AI answer from your own documents: it first finds the relevant passages, then writes its answer based on them.

U

  • Use case

    A specific task, with a measurable gain, where data or AI is applied. You pick a few, starting with those that pay back the most.

    AIGovernance and securitySee: Audit & consulting

W

  • Web scraping

    A program that reads web pages and puts the useful information into a table or into your tools.

    DataAutomationSee: Data & documents
  • Workflow

    An automated sequence of steps: a trigger (an email arrives), some processing, then an action (the file is updated, the right person is notified).

Where to start?

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