MANUFACTURING

AI on the shop floor without losing the IP.

Maintenance technicians get a copilot that reads the manuals and the work-order history. Quality teams get root-cause analysis on defects that used to take days. Procurement gets supplier RFQ analysis at the speed of buying. All inside the plant network — designs and BOMs never leave.

Manufacturing's AI moment hinges on two truths regulators and consultants rarely both name. First: the productive workforce is ageing, retiring with institutional knowledge that the next generation won't accumulate over the same decades. Second: shop-floor systems hold the deepest IP a manufacturer owns — designs, processes, supplier terms — and that IP cannot drift to a public cloud.

Generative AI is well-suited to capturing the first kind of knowledge into agents that surface it on demand: maintenance how-to's, troubleshooting runbooks, supplier price negotiation patterns. But the deployment has to live inside the plant or the plant network, not in a vendor cloud that processes prompt content for retraining.

The regulatory frame is also tightening. EU Machinery Regulation (EU 2023/1230) applies from January 2027 with new obligations for safety functions that include AI components. NIS2 brings OT environments into scope of cyber incident reporting. CSRD requires reportable narratives that span every plant. Kosmoy is the operating layer that lets manufacturers ship AI on the shop floor while honouring all of it.


What this industry runs into.

OT / IT separation

Plant control networks are intentionally isolated from corporate IT. AI tooling that requires constant egress to the cloud doesn't fit. The platform has to live inside the plant or the manufacturer's private cloud.

IP protection

BOMs, CAD references, supplier terms, process recipes — these are the manufacturer's most sensitive data. Sending them to an LLM provider for prompt processing is, for many firms, an immediate non-starter.

Skilled labour shortage

Senior maintenance technicians and quality engineers are retiring faster than juniors can be trained. Agents that capture the senior's troubleshooting flow are an institutional answer, not a productivity gimmick.

Plant-by-plant variation

Two plants on the same product line can have different equipment, different work instructions, different standard operating procedures. A single global agent doesn't fit; per-plant agents with shared infrastructure do.


Regulatory landscape.

The regulations that shape AI in manufacturing — and where each one bites on AI deployment.

ISO 9001Quality management systems· Global

QMS-relevant decisions made or supported by AI must remain auditable. CAPA workflows that incorporate AI need traceable evidence of how the AI contributed.

EU Machinery RegulationRegulation (EU) 2023/1230· EU

Applicable from January 2027. AI components in safety functions are explicitly addressed. Conformity assessment includes AI risk management.

NIS2Network and Information Security Directive 2· EU

Manufacturing of critical products and chemicals is in scope. AI infrastructure that touches OT must meet incident reporting and risk management obligations.

CSRDCorporate Sustainability Reporting Directive· EU

Reporting narratives drafted with AI assistance must remain factually accurate to the underlying data. Lineage matters; so does the audit trail.

REACH / RoHSRegistration, Evaluation, Authorisation and Restriction of Chemicals / Restriction of Hazardous Substances· EU

AI agents that screen materials and substances must be auditable; the substance allowlist drives a hard policy boundary.

ISO/IEC 42001AI Management System Standard· Global

Manufacturers seeking AI governance certification map their platform to ISO 42001 controls. Inventory, risk assessment, monitoring all required.


Use cases that are actually shipping.

Maintenance technician copilot

Technician picks up a CMMS work order for a packaging line conveyor that's tripping. The copilot on the tablet reads the work-order context, the equipment manual (often in German or Italian), the past 12 months of repair history on this asset, the OEM service bulletins, and drafts a step-by-step troubleshooting plan. It surfaces the LOTO (lockout/tagout) requirements before the technician approaches the equipment.

MTTR (mean time to repair) drops 25–35% on the lines where the copilot is deployed. Junior technicians close work orders at senior productivity within their first six months — the agent carries the institutional knowledge.

Quality root-cause analysis

Quality engineer flags a defect spike on a stamping line. The agent reads the SPC data, recent production logs, operator notes, machine alarms, raw material batch records and the defect images, and proposes ranked candidate root causes — die wear, material variation, operator setup, environmental humidity. The engineer investigates the top candidate; the agent doesn't decide.

Time-to-root-cause on yield issues drops from 2–5 days to hours on common defect modes. CAPA quality improves because the agent's evidence chain is preserved.

Supplier RFQ analysis

Procurement issues an RFQ for a 200-line BOM and gets responses from 8 suppliers in different formats — PDFs, spreadsheets, scanned faxes. The agent extracts each line, normalises units and currencies, identifies cost arbitrage opportunities and flags lines where suppliers quoted obsolete part numbers. Procurement reviews ranked findings.

RFQ analysis time drops from a week to a day for a typical 200-line response set. Cost arbitrage capture rises 5–10% because the agent surfaces opportunities humans missed at scale.

MES / shop-floor copilot

Shop floor supervisor: 'why is line 3 throughput down 12% this shift?'. The agent reads MES output, machine alarms, operator hand-offs, raw-material status and quality holds, and drafts a structured response: line-3 OEE breakdown, top three contributing factors, and the recommended next investigation step. Supervisor decides where to allocate attention.

Supervisors react to throughput shortfalls within the shift rather than at the morning standup. Daily OEE rises 1–3 points on lines where the copilot is in use.

CAPA (Corrective and Preventive Action) drafting

Quality event triggers a CAPA. The agent drafts the CAPA record from the underlying QMS event, similar past events, regulatory expectations and the firm's CAPA template. Quality engineer edits, adds investigation outcome, signs. Cycle time on standard CAPAs drops sharply.

CAPA backlog reduces 30–50% within six months. Audit findings on CAPA quality improve because the structure and evidence chain are consistent.


Agent governance

Where manufacturing agents need extra discipline.

Manufacturing agents touch the deepest IP and the most safety-critical systems on the floor. Kosmoy's Agent Registry binds each agent to its plant, its allowed equipment and its allowed actions. A maintenance copilot at one plant doesn't read another plant's recipe book; an agent that suggests work orders cannot dispatch them automatically without explicit authorisation.

The Action Capsule shows up here for the agents that interact with MES, CMMS or SCADA-adjacent systems. Pre-flight authorisation enforces that the agent can read the work-order system but only write back through the approved API path. The Insights Dashboard surfaces patterns: which copilots accelerate junior technicians, which agent versions correlate with lower MTTR, which retrieval scopes need expansion.


Chatbot use cases

Chatbots, by surface and risk class.

Manufacturing chatbots are dominantly internal. Customer-facing presence is small (B2B procurement portals, after-sales technical support); the larger surface is operations-facing — maintenance crew, quality, planning, procurement, EHS, plant management.

EHS / safety helpdesk

Operator asks 'do I need additional PPE for handling this solvent?'. Agent reads the SDS and the firm's EHS protocols, returns a citation-grounded answer with the relevant SDS section.

Plant manager dashboard Q&A

'What's our scrap rate trend over the last quarter on line 4?'. Agent reads the MES + quality data, drafts a structured answer, attaches the chart.

After-sales technical support

Customer service rep handling a B2B equipment customer call asks the agent for the firm's troubleshooting playbook on a specific failure mode. Citation-grounded answer with the right service bulletin.

Onboarding agent

New hire asks 'how do I run a setup change on line 6?'. Agent retrieves the SOP and walks through it. Never invents a step the SOP doesn't include.


How Kosmoy fits.

Manufacturing benefits from Kosmoy's deployment model more than most: on-prem and per-plant Kubernetes clusters work well for OT-adjacent installations. The AI Inventory captures every agent across plants — useful when CSRD or NIS2 reporting demands a single view. The Gateway centralises model access so that fine-tuned SLMs running on a plant GPU live alongside frontier models gated for non-IP-sensitive uses.

The economics of running open-weight models on plant-local GPUs versus paying frontier-model rates per call are decisive at manufacturing volumes. Kosmoy's LLM Router routes simple maintenance Q&A to the local SLM and reserves frontier capacity for the harder root-cause cases. Cost Tracking attributes every call to the plant, line and shift.


Module questions, answered straight.

Can we run a per-plant install?

Yes. The standard pattern is a per-plant or per-region install with a federated AI Inventory at the corporate level. Plants run independently when corporate connectivity is intermittent; central governance has visibility when it isn't.

Does Kosmoy support open-weight models on plant GPUs?

Yes — and most manufacturers run this way. Llama, Mistral, fine-tuned SLMs all run on plant-local vLLM/Ollama. The Gateway treats them as private providers; the Router decides which model serves which prompt.

How do we handle the EU Machinery Regulation AI provisions?

Agents that contribute to safety functions are registered in the AI Inventory with their conformity assessment status and the safety function they support. Risk Classification runs the EU AI Act flow on each. The dossier the regulator asks for is generated, not assembled in panic.

Will the maintenance copilot replace technicians?

No. The copilot accelerates technicians and captures senior-technician knowledge so junior staff ramp faster. Decisions to run a procedure, restart a line or escalate a safety issue stay with the human technician.

Bring AI to the shop floor without losing the IP.

See how Kosmoy runs agents on plant-local infrastructure, contains them in Action Capsules, and keeps designs and recipes inside the perimeter.