# AI in manufacturing: real examples for mid-sized firms > Technical documentation queried in plain language, tenders prepared, invoices and contracts checked, in-house tools rebuilt: concrete examples of AI in manufacturing for mid-sized companies. URL: https://aiorigin.io/en/secteurs/industrie - Industries - Manufacturing INDUSTRY · MANUFACTURING # AI in manufacturing: your experts find information faster. Manuals, failure history, sales references, contracts: we connect your ERP and your documents to AI, with trade secrets protected. Your technicians, sales reps and buyers decide. Talk about your project See how it works A 30-minute conversation with the team that will run your project, with no commitment. - Bridgestone: AI workshop and keynote for the teams - Trade secrets protected AI IN MANUFACTURING For Shop floor, sales, purchasing Who decides Your experts Updated October 15, 2026 THEY TRUST US - Celio - Plein Sens - Shiseido - Green-Got - Promologis - Bridgestone IN BRIEF ## What are examples of AI in a mid-sized manufacturer? Beyond predictive maintenance, which requires sensors and factory data, the uses quickest to put into service concern information: finding the right procedure in hundreds of manuals, preparing a tender response from your references, checking invoices and contracts, reporting on field sales visits. They rely on your documents and your ERP, with one simple rule: every answer cites its source, and the technician, the sales rep or the buyer decides. France’s Direction générale des Entreprises has published a guide on this approach (RAG) applied to company documents. FIVE EXAMPLES Technical documentation · Tenders · Invoices and contracts · Sales visit reports · Rebuilt in-house tools. - Executive management - Manufacturing management - Sales - Purchasing - IT Updated October 15, 2026. WHAT YOUR TEAMS FACE ## The information exists, no one can find it. What manufacturing and sales leaders tell us. PLANT “The right procedure is somewhere in the manuals, or in a veteran’s head.” TENDERS “We turn some down for lack of time to study them.” TOOLS “Our in-house tool doesn’t talk to anything else.” WHO IT’S FOR - Executive management - Manufacturing management - Maintenance - Sales - Purchasing EXAMPLES ## AI prepares, your experts decide. Uses connected to your documents and your ERP, with the source of every answer. ### Failures analyzed before the repair AI cross-checks manuals, failure history and field feedback. The technician validates, then repairs. ### More tenders reviewed AI finds your references and prepares a first response. Your sales reps price and sign. ### Invoices and contracts checked AI matches orders and invoices, then flags risky clauses. The buyer or the lawyer decides. ### Sales visits in the CRM The sales rep dictates on the way out; the report is filed, after review. ### In-house tools rebuilt Your quoting or deal-tracking tool, rebuilt AI-ready. ### Teams trained on their own cases In a hands-on session, everyone leaves with an agent that solves a real problem. AI-READY ### Your AI agents read and act in the tool, through MCP. MCP is an open standard: a universal plug, under your control, between your software and AI. Your IT department approves every access. - SAMPLE REQUESTS TO YOUR AGENTS - “Which procedure for this fault code on line 3?” - “Find our references for this type of contract.” - “Which invoices don’t match the order?” BEFORE / AFTER ## What changes for your teams. Before and after: Manufacturing TODAYWITH AI, APPROVED BY YOUR TEAMS ProceduresSearched for in binders.Found with one question, with the source. TendersTurned down for lack of time.First response prepared from your references. InvoicesSpot-checked.Matched against orders, discrepancies flagged. Every gain is measured in your company, from your starting point. OUR METHOD ## Four steps, from the shop floor to headquarters. The four steps of our method, in a loop. Each can be done on its own; together, they organize AI across the whole company. ### Inspire your leadership team A keynote built on cases from your business. Your leadership decides where AI will be useful, and where it will not. ### Map your operations We spot the bottlenecks, rank use cases by gain and difficulty, and name the tools to keep. ### Bring your teams on board In a hands-on session, everyone arrives with a real problem and leaves with the AI agent that solves it. An AI policy sets the shared rules. ### Build with the AI Factory Our engineers build AI-ready business tools with you. You keep the keys. ### You take back the keys. The code and data stay with you, documented. We keep improving the tool with you, or you take it over. This is step 4 of our method: Build with the AI Factory. YOUR QUESTIONS ## What manufacturers ask us. What are concrete examples of AI in manufacturing? An assistant for technical documentation, preparing tender responses, matching invoices and orders, field sales visit reports, and rebuilding in-house tools AI-ready. Where should a mid-sized manufacturer start? With a keynote for leadership and a map of operations: we choose a first useful use case, quick to put into service, then extend. Do you need sensors and factory data to get started? No. The first uses rely on your documents, your ERP and your tools. Predictive maintenance is a different, longer project. Does the AI Act apply to industrial AI? An internal document assistant is generally not a high-risk system. AI systems built into regulated products, such as machinery, follow specific rules. How do we connect AI to our ERP? Through connectors approved by your IT department, including MCP. If your in-house tool does not allow it, we can rebuild it AI-ready. Do our drawings and confidential documents stay protected? Yes: hosting chosen by you, access rights by team, and no model training on your data. Does AI decide in place of your teams? No. AI prepares: it sorts, checks, summarizes and writes a first draft. A named person reviews and decides. Every AI action is logged. SOURCES ## The texts and studies cited on this page. Every figure on the site is sourced. See all our sources. Direction générale des Entreprises, Guide de la génération augmentée par récupération (RAG), November 2024. entreprises.gouv.fr Union européenne, Règlement (UE) 2024/1689 sur l’intelligence artificielle (AI Act), June 13, 2024. eur-lex.europa.eu Insee, Insee Première n° 2120, July 21, 2026. insee.fr LET’S TALK ABOUT YOUR PROJECT ## Let’s talk about your teams. Thirty minutes to understand your priorities, and tell you where we would start. Your contact The AI Origin team that runs the projects You talk directly with the people who will run your project, from scoping to go-live. No specific project yet? Start with a hands-on session: everyone brings a real problem and leaves with the AI agent that solves it. See step 3, Bring your teams on board Thank you, we have received your request. We will get back to you to schedule a time. ### Write to us in two lines. Your company, your sites, the teams involved. We will get back to you to schedule a time. Write to contact@aiorigin.io Or book a time slot Or write to us: contact@aiorigin.io