AI that supports your frontline teams
Scattered technical documentation, recurring complaints, a supplier base never compared in full: GENIAL gives manufacturers AI agents that make company know-how available in a single question.
8
role-specific agents ready to work on your processes
2–3 wks
to scope your priority use cases
€4,000
Bpifrance grant toward your AI assessment
50,000+
employees already empowered by Genial, across industries
Your pain points
What AI changes in your day-to-day
Technical documentation
Drawings, routings, product sheets, quality procedures: the information exists, split across the ERP, the document management system and network drives, with thirty years of different naming conventions.
Recurring complaints
The same nonconformities come back every year without ever being traced to a product line or a plant.
The supplier base
Your buyers renegotiate the twenty most visible contracts because there's no time to read the other three hundred before a sourcing campaign.
Know-how heading into retirement
Machine settings written down nowhere live in three people's heads, and the handover comes down to a few weeks of overlap.
Quoting jobs
Every request for quote means digging up a comparable job, its assumptions and its actual margin. The quote goes out without that perspective.
Product standards
The Machinery Directive, REACH, CE marking, customer requirements: checking what applies to a part number takes hours of cross-reading.
Already transforming their business
Manufacturers from mid-market companies to multi-site groups, from mechanical engineering to capital equipment.
Automotive supplier
Geni (General)Technical documentation available in one question
drawings, routings and procedures, without switching tools
Mid-market manufacturer
Geni-SupportComplaints traced to their root cause
recurring issues linked to production lines
Precision engineering group
Geni-ProcurementThe entire supplier base compared
before every renegotiation campaign
Capital equipment manufacturer
Geni-HRRetiring experts' know-how captured
settings and hands-on tricks finally written down
In the field
Three situations, three answers
Shop floor · changeover
What are the approved setup parameters for this part number on line 3?
Parameters from the last conforming run, a gap flagged against the theoretical sheet, and the checkpoint that caused trouble last time. Sources cited, for the setup technician to confirm.
Quality · monthly review
Which nonconformity reasons have come up most in the past six months, and on which lines?
Three reasons accounting for most complaints, traced to two part numbers and one plant, with the matching service reports to investigate the root cause.
Procurement · before renegotiation
Compare the terms of all our suppliers in this category.
Negotiated terms by supplier, renewal dates over the next twelve months, price gaps between comparable parts and missing price-adjustment clauses.
In partnership withAI assessment: a €4,000 grant to get your program started
GENIAL is an accredited AI Expert for Bpifrance, France's public investment bank. Its Diag Data & IA program funds your assessment: a map of current AI use, priority use cases and a roadmap.
Industry questions
Our operators don't have computers. How do they use it?
Access also works from a phone or a shop-floor tablet, in plain language. Operators ask their question the way they'd ask a coworker, with no software training.
Can the agent read our drawings and technical documents?
Yes, including scanned PDFs and office documents in your document management system. Documents stay where they are: the agent reads them, it doesn't move them.
What happens when the agent doesn't know?
It says so instead of making something up. Every answer cites the internal documents it used, so operators can check the source before acting on a machine.
Can our production data leave the company?
No. Hosting is in Europe, your data is never used to train models, and access rights match those of your source tools, plant by plant.
Can we start with a single plant?
Yes, and we recommend it: one pilot plant for a quarter, with usage metrics tracked weekly, then a rollout across the group once the results are measured.
Make your plant's know-how available to everyone
Thirty minutes to pinpoint the two tasks that cost your teams the most time, and what AI can really change there.
