FORMATION IA
Assistant de Devis IA pour Ateliers de Fabrication
Repartez avec un outil IA opérationnel qui lit les PDFs clients et rédige des devis à partir de vos anciens travaux.
Ce qu'elle couvre
Un atelier intensif d'une journée où les chargés de devis et commerciaux de petits fabricants construisent un assistant de devis fonctionnel grâce à l'IA. Les participants connectent un modèle de langage à leurs données d'historique de jobs, configurent l'extraction de spécifications depuis des PDFs, et génèrent automatiquement des ébauches de devis structurées. En fin de journée, chaque équipe repart avec un prototype utilisable immédiatement — aucune compétence en programmation requise. La séance alterne courtes introductions conceptuelles (30 %) et temps de construction guidé (70 %).
À l'issue, vous saurez
- Configure an AI tool to extract key specs (dimensions, materials, tolerances) from a customer PDF quote request
- Build a prompt template that references historical job costs to produce a structured first-draft quote
- Apply a review checklist to catch AI errors before sending a quote to a customer
- Export or integrate the quoting assistant output into an existing spreadsheet or ERP workflow
- Identify the job types where AI-assisted quoting saves time versus where human judgement must take over
Sujets abordés
- Extracting specs and dimensions from customer PDF drawings using AI
- Structuring and querying historical job cost data as an AI reference
- Prompting a language model to generate a first-draft quote
- Reviewing, editing, and approving AI-generated quotes safely
- Handling edge cases: missing specs, unusual materials, first-time jobs
- Basic data hygiene for past-job records used as AI input
- Connecting the tool to a shared folder or simple spreadsheet workflow
Modalité
Delivered in-person at the client's site or a training facility; remote delivery is possible with participants sharing screens. Participants work in pairs on real or anonymised company data. Facilitator provides a pre-built starter template and a no-code AI environment (e.g. a configured GPT or a Make/Zapier workflow). Materials include a PDF extraction guide, prompt library, and a post-workshop checklist. Hands-on build time represents approximately 70% of the day.
Ce qui fait que ça marche
- Starting with a narrow, well-defined job category (e.g. laser-cut steel brackets) before expanding scope
- Assigning one internal owner who maintains the historical job dataset and prompt templates
- Pairing the AI draft with a mandatory estimator sign-off before any quote leaves the building
- Running a 4-week pilot on real incoming RFQs and tracking time-to-quote and error rate
Erreurs fréquentes
- Feeding the AI poorly formatted or inconsistent historical job data, producing unreliable quote drafts
- Sending AI-generated quotes to customers without a human review step, causing pricing errors
- Trying to automate every job type on day one instead of starting with the 20% of repeat jobs that represent 80% of volume
- Neglecting to update the historical job dataset regularly, causing the AI to quote based on outdated material costs
Quand NE PAS suivre cette formation
A job shop where every order is fully custom with no historical comparable jobs — the AI has nothing to learn from and will produce unreliable drafts that take longer to correct than to write from scratch.
Fournisseurs à considérer
Sources
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