Customized professional training
AI training for research teams
Accelerate literature review, results analysis and scientific valorization without compromising rigor.
Starting from €1,500 excluding VAT per half-day · Written proposal within 24 working hours, without obligation.
The training in brief
Everything you need to make a decision, in nine lines. The objectives, process, and use cases are below.
- What it is
- A customized training in generative AI For research teams: a maximum of twelve participants, each working on their own computer, focusing on their own topics. No lectures or demonstrations: 70% hands-on practice.
- What we work on there
- Your literature reviews and analyses : querying a scientific corpus with its references, writing clear and testable requirements, monitoring publications and patents, promoting the results.
- For who
- The teams research, science and R&DAll levels, including employees who have never opened the tool.
- Duration and rhythm
- 1 hour 30 minutes or half a dayAvailable in one go or in waves of sessions to cover the entire team. Also available as a webinar.
- Where and in what language
- At your premises anywhere in France, or remotely. French or English.
- Price
- €1,500 to €2,000 excluding VAT Half-day sessions for up to twelve participants, with a sliding scale of prices when sessions are repeated. See our price benchmarks.
- On which tool
- Yours: Copilot, ChatGPT, Claude, Gemini, Mistral or your secure internal assistant. We train within your tenant, without third-party tools.
- Funding
- Eligible for OPCO and ESF+ funding. NextStart is a registered training organization (No. 11756140675): the session is part of your skills development plan, with the agreements and documents expected by your funder.
- Lead time
- Written proposal within 24 business hours, without obligation, after a 30-minute framing exchange.
Why train your research teams in generative AI?
Researchers can accelerate certain documentary and exploratory tasks without compromising scientific rigor, source traceability, or research integrity.
A very extensive body of scientific literature
Identifying, classifying and comparing relevant publications requires an explicit and reproducible method.
Results that are complex to interpret
AI can offer angles of analysis, but the methods, calculations and conclusions must remain verifiable.
This work should be promoted to several audiences.
Articles, summaries, reports and presentations require different levels of precision without distorting the results.
Sensitive data and ideas
Unpublished data, protocols, and intellectual property require a suitable environment and rules.
What your research teams will be able to do upon exit
Six objectives, assessed during the session on the files that your teams bring.
- Develop a literature search strategy on a specific scientific question, then produce a literature review in which each statement is supported by a verified reference.
- Structure the analysis of a set of experimental results and derive three competing interpretations, along with what would allow one to distinguish between them.
- Write and revise a scientific text (abstract, methods section, response to reviewers) using an AI tool, then check its accuracy and scope before submission
- Adapting the same research result to three recipients (peer-reviewed journal, funding body or program committee, popular science article) without changing its meaning
- Recognizing in an AI output an invented reference, a distorted quote, or a conclusion that is not supported by the data
- Apply your internal usage rules, the GDPR, and Section 4 of the AI Act to your own records
How we prepare the session with your scientific advisor
The content, examples and tools are prepared with your subject matter expert before the session.
Feasibility study
Gathering of needs, participant level, constraints and priority use cases.
Customization
Adaptation of the schedule, demonstrations and exercises, then validation with your organization.
Training
Participatory facilitation, guided practical application and distribution of educational materials.
How generative AI is transforming research professions
AI can accelerate literature searching, synthesis, and results exploration. It becomes useful when it enhances researcher rigor, source traceability, and the ability to challenge interpretations.
Explore literature more quickly
AI helps to formulate research directions, organize sources and compare works before in-depth reading.
Summarize without losing the evidence
Large corpora can be structured into themes, arguments and results while retaining the references necessary for verification.
Analyze data and assumptions
AI can help to uncover trends, anomalies and alternative hypotheses, which the researcher must then test and interpret.
Maintaining rigor and traceability
Each use must distinguish between facts, inferences and suggestions, avoid invented quotations and protect sensitive research data.
The program, hour by hour
A balance designed to understand, practice and then secure uses in the work environment.
Schedule for the half-day (3 hours 30 minutes)
- 0 p.m. to 00 p.m. Fundamentals of generative AI applied to research, getting to grips with the chosen tool, personalized memory and instructions, modes of reasoning and in-depth research, demonstration on a scientific question provided by the team.
- 0 p.m. to 20 p.m. : method of prompting on a scientific corpus, construction of a documentary search equation, and procedure for verifying the references cited by the tool.
- 0 p.m. to 40 p.m. : Prompts and Agents workshop, first block, on your own topics: state of the art of a research question, comparison of contradictory publications, exploration of a set of results and formulation of alternative hypotheses to test.
- 2 p.m. to 40 p.m. Prompts and Agents workshop, second block: scientific writing and revision (summary, methods section, response to reviewers), popularization towards a funder or a program committee, and construction of a publications and patents monitoring agent.
- 3 p.m. to 10 p.m. : bias and limitations of models, invented references and scientific integrity, confidentiality of unpublished data and pending work, GDPR, Article 4 of the AI Act and collective drafting of your rules of use.
The 1 hour 30 minute format follows the same tight structure: 20 minutes of fundamentals, 55 minutes of workshop on two chosen cases, 15 minutes of usage framework.
The research situations we can work on
The exercises are selected according to your priorities. The groupings below retain the details of the situations that can be worked on.
State of the art
- Building a research strategy
- Synthesize scientific articles
- Compare multiple publications
- Mapping the debates and gaps
Monitoring and patents
- Prepare a scientific monitoring
- Explore patent databases
- Identify related teams and projects
- Detecting emerging trends
Hypotheses and protocols
- Generate testable hypotheses
- Challenger an experimental protocol
- Identify the variables and possible biases
- Prepare an analysis plan
Analyze results
- Explore a dataset
- Detect anomalies and trends
- Compare several interpretations
- Prepare relevant visualizations
Scientific writing
- Structuring an article
- Improving a summary or abstract
- Prepare a response to the reviewers
- Check the argumentative coherence
Valorization
- To popularize the results
- Prepare a conference presentation
- Write a memo for decision-makers
- Explore technological applications
Concrete examples of use cases for research teams
Resources to extend training in research, synthesis and documented analysis.
Preparing an application for a call for projects →
Prepare the compliance grid, the technical file and the budget for an application.
Write clear and testable requirements →
Reformulate a need into verifiable requirements, without ambiguity of interpretation.
AI Analyst of Scientific Articles and Patents →
To query a scientific corpus and extract the useful elements with their references.
Scientific monitoring and patents →
Follow publications and filings in a domain and receive a periodic briefing.
Monitoring calls for projects and funding →
Identify relevant calls for projects and their submission deadlines.
Building a state-of-the-art overview from start to finish →
To frame the research, collect the sources and produce a documented synthesis.
Summarizing a long document without losing the evidence →
Extract the essential information while retaining useful passages and references.
Clarifying a vague request before proceeding →
Define the scope of a study request before committing research time.
Taking over an inherited file →
Reconstructing the history of a project that was taken over mid-course.
Making a legacy Excel file more reliable →
Map out what a critical workbook calculates and make it transmissible.
Your data does not leave your environment
Unpublished results, experimental protocols, work in progress being submitted: your research data does not leave your environment.
The exercises are based on your real-world situations, never on your actual data. We develop the practical cases with your business expert using anonymized or reconstructed examples, and we work within the environment approved by your IT department: Copilot Chat, Copilot M365, ChatGPT (Enterprise or Azure OpenAI), Gemini, Claude, Mistral, or a locally installed open-source solution for the most sensitive data. No documents, files, or personally identifiable information are transmitted to a public model during the session. The final part of the training is dedicated to GDPR, the AI Act, and the development of your internal usage rules, ensuring that each participant leaves with a clear understanding of what they can and cannot submit to an AI tool.
Copilot M365
Claude
ChatGPT
Gemini
VibeReferences and feedback
Some examples of interventions and feedback from NextStart.AI training courses.
Airbus470 participantsAirbus595 participants
CNES673 participants
Alptis450 participants31 AI Champions
Agirc-Arrco650+ participants
Bristol Myers Squibb237 participants10 AI Champions
Ceva Animal Health209 participants
SATT network173 participants
Cerema145 participants
Engie11 participants
AÉSIO mutual21 participants
Crédit Mutuel13 participants
Customer reference
Professional training in generative AI
"Constructive exchanges / Relevant examples / Practical application"
Frequently asked questions about AI training for research teams
Answers to key questions about level, tools, personalization, and modalities.
Do you need to already know how to use ChatGPT or Copilot?
No. The content is adapted to the level of the participants, from discovery to more advanced methods.
Can the training use our internal tool?
Yes. The session can use the tool approved by your IT department, including Copilot, ChatGPT (Enterprise or Azure OpenAI), Gemini, Claude, Mistral or a local solution.
Can we work on our own use cases?
Yes. Priority situations are selected with your contact person, then transformed into suitable and safe exercises.
What is the difference between the 1 hour 30 minute format and the half-day format?
The shorter format focuses on familiarization and a few demonstrations. The half-day format allows for more hands-on practice with your specific use cases.
Can the training be funded?
Our training courses are eligible for OPCO and ESF+ funding.
Can AI perform a reliable literature review?
It can help to explore, classify and synthesize, but each reference must be found, read and verified in a scientific source.
Can unpublished research data be used?
Only in an environment authorized by your organization and in accordance with applicable confidentiality, security, and integrity rules.
How much does the training cost?
The price depends on the chosen format, the number of participants, and the number of sessions. We will send you a quote within 24 business hours of our initial discussion. Price ranges for standard formats can be found on the Corporate AI Training page.
How soon can a session be organized?
Allow one to two weeks between your agreement and the session, the time needed for framing with your scientific advisor, personalization of exercises and validation of the schedule.
What deliverables do the participants receive?
A booklet of about fifty pages, the prompts and agents built during the workshop on your own cases, and the rules of use written collectively at the end of the session.
Let's build your customized research training
Describe your situation in a few lines. We will get back to you within 24 business hours with a proposal tailored to your teams, tools, and schedule.
Do you prefer to call or write? +33 1 89 16 48 05 or hello@nextstart.aiYour contact details are only used to reply to you.
NextStart is a training organization registered under number 11756140675. This registration does not constitute state approval.