Your processes are specific
An off-the-shelf tool imposes its data model and its assumptions. Your product ranges, your rules and your business vocabulary only half fit. A custom system starts from your reality, not from an average case.
Industrial AI systems engineering
We design custom systems that solve your industrial problems.
Assets 4.0 is an engineering firm. We design, build and deploy custom business systems and infrastructure for industry; AI is the engine when it delivers real value. Co-designed with your teams or delivered turnkey. Not chatbots: systems that hold up in production.
Architecture & development
Local and sovereign AI
Integrated with your business tools
Designing an industrial AI system means starting from a precise business problem, designing its architecture, choosing and assembling the right models, then developing, integrating and deploying a solution that runs in production. Assets 4.0 works in two ways: co-design, as an AI engineering office alongside your experts, or turnkey, taking on the project from study through to go-live. Our domains cover AI agents, business applications, document AI, industrial vision, automation and local AI. We do not sell chatbots: we design systems that solve complex problems.
Why custom
Why design a custom AI system?
Generic tools are built for an average case. Your plant, your data and your constraints are not average. A system designed for your context does exactly what you need, and nothing useless.
Integration decides everything
A useful system talks to your ERP, your CMMS, your MES, your SharePoint and your document stores. Closed tools integrate poorly. We design integration from the architecture stage, not as an afterthought.
Data sovereignty
Your data describes your processes, your defects, your know-how. Much of it cannot leave the company. We design systems that process your data where it sits, locally when needed.
Real industrial constraints
Offline operation, controlled response times, closed network environment, embedded hardware. These constraints are handled at design time. A system built for them works where a consumer tool fails.
You keep control
A SaaS subscription makes you dependent on a third party, its model and its roadmap. A system designed for you stays yours: code, data and future changes under your control.
Value that lasts
A prototype impresses, then stops. A system built to last is maintained, corrected and evolves with your needs. That is the difference between a demonstration and a tool that stays in service.
Option 1 · Co-design
Designing with you
You bring the business expertise and the knowledge of the field. We bring the AI architecture, the models, the workflows, the integrations and the deployment strategy. We act as your AI engineering office, alongside your teams.
Scoping workshops
We start from your experts and your processes. Together we frame the decision to improve, the available data and the constraints, then derive the scope of the first system.
System architecture
We design the technical architecture: data sources, models, flows, security and integration points. It is the blueprint that ensures a prototype can become a production system.
Models & data
We select and assemble the models suited to your case: language, vision, extraction, prediction. We prepare your data and calibrate the system on your real examples, not on demonstration cases.
Business validation
Your experts judge the results at every step. We adjust with them until the system is reliable on the cases that matter. Trust is built on examples your teams know.
Rapid prototypes
We quickly build a prototype on your real data, to settle feasibility before any heavy development. You see the system work early, and you decide on something concrete.
Skills transfer & evolution
We transfer ownership to your teams: documentation, training, readable code. The system stays yours, extensible, and you can take it over, extend it or hand it to a third party.
Option 2 · Turnkey
Designing for you
You describe the need. We deliver a ready-to-use solution: study, design, development, architecture, integrations, deployment and go-live. You follow progress, we carry the engineering end to end.
StudyWe analyse the need, the data and the constraints, and frame the expected outcome.
DesignWe define the system's architecture, models and flows.
DevelopmentWe build the system, tested on your real cases.
IntegrationsWe connect it to your tools: ERP, CMMS, MES, document stores.
DeploymentWe put it into service on your infrastructure, on-premise or in a private cloud.
SupportWe monitor, fix and evolve the system over time.
Our engineering domains
What we design
Six AI engineering domains, combined to suit your need. A single project often draws on several: an agent that reads documents, integrates with your CMMS and runs locally.
AI agents
Agents that carry out business tasks end to end, with access to your data and your tools.
MaintenanceQualityProductionInspectionSupply chainProcurementHRSalesAfter-salesDocumentation
AI applications
Software and applications that embed AI at the heart of daily work, on desktop, tablet or mobile.
Business softwareSaaSTablet appsMobilePortalsCopilots
Document AI
Extract, structure and query the information held in your documents, whatever their format.
PDFReportsAuditsProceduresContractsEDMDocument stores
Industrial vision
Analyse images to inspect, detect, classify and read, in-line or during inspection campaigns.
Image analysisOCRDetectionClassificationQuality control
Automation
Connect your systems and automate repetitive tasks between your tools, with no double entry.
ERPCMMSMESAPISharePointMicrosoft 365SAPn8n
Local AI
Run AI on your own infrastructure, with no data sent outside, for sovereignty and latency.
Local LLMsGPUPrivate cloudOn-premise deploymentData sovereignty
Our methodology
From idea to a production system
An engineering method, not a promise. Each step produces a deliverable that lets you decide on the next.
1DiscoveryThe problem and the decision to improve.
2Business analysisData, processes and real constraints.
3ArchitectureModels, flows, security, integrations.
4PrototypeFeasibility proven on your data.
5DevelopmentBuilt on your real use cases.
6ValidationReliability checked with your experts.
7DeploymentOn-premise or in a private cloud.
8EvolutionMonitoring and improvement over time.
Example deliverables
What we can design
A few typical systems. The list is not closed: if an industrial problem exists, it can be designed for.
Maintenance AI agentShutdown preparation, intervention prioritisation.
Quality AI agentNon-conformities, action plans, traceability.
Inspection AI agentAnalysing NDT reports, tracking findings.
QHSE AI agentCompliance, incidents, regulatory documents.
Document AI agentSearch and answers across your EDM.
Technical assistantA copilot for your field teams.
Document search engineSemantic search across your archives.
Industrial copilotDecision support at the workstation.
Business softwareA custom application driven by AI.
AI visionAppearance inspection and in-line detection.
Document extractionStructured data from PDFs.
Decision platformIndicators, priorities and alerts.
Our technology building blocks
Building blocks, chosen for your project
We don't start from an imposed tool. We select and assemble the building blocks suited to your need, your constraints and your budget. Here are the ones we use most often.
AI capabilities
LLMVisionRAGAgentsMCPExtraction
Models
ClaudeGPTGeminiMistralQwenLlamaOllama
Development & infrastructure
PythonFastAPIDockerPostgreSQLSupabaseAPIn8n
The right system is not the one that uses the trendiest technology, but the one that assembles the right building blocks for your problem. The choice is made during scoping, never in advance.
Sectors
The industries we serve
We work with industries where data, compliance and process integrity are critical.
Food & beverage
Pharmaceutical
Cosmetics
Automotive
Aerospace
Energy
Nuclear
Chemicals
Logistics
Manufacturing
Medical
Construction
Our difference
An AI engineering firm, not an agency
The difference is what we carry: an architecture, execution all the way to production, and a system you keep. Where many stop at the prototype or bill day rates. When the regulatory framework requires it, design extends into an AI compliance audit.
Assets 4.0
AI agency / IT services firm
Starting point
An industrial problem and a decision to improve
A technology or a catalogue of tools
Target deliverable
A system in production, used every day
A prototype or a demonstration
Architecture
Designed and owned
Often absent
Business integration
ERP, CMMS, MES from the design stage
Handled afterwards, if at all
Local & sovereign AI
Yes, when required
Cloud by default
Ownership
Code and data are yours
Vendor lock-in
Architecture & industrialisation
We design for production, not for demonstration: robustness, maintainability, scaling.
Simplicity & integration
A lean system that fits into your existing tools and that your teams adopt without friction.
Security, local AI & scalability
Local processing when needed, security designed in from the start, and a system that evolves with your needs.
Our work · example
Lucens Integrity, a system we designed and built
To illustrate what we can do, here is an industrial AI system we designed and built end to end: an Asset Integrity Intelligence platform that analyses inspection reports, rebuilds the history of each piece of equipment and makes it steerable, all processed locally. It is an example of what we can do, not the subject of this page.
Frequently asked questions
What decision-makers ask us
Why work with you rather than an AI agency or an IT services firm?
A typical AI agency often stops at a prototype or a chatbot, and an IT services firm often works on a day-rate basis, without necessarily owning the architecture or the system's upkeep over time. We are an AI engineering firm: we design the architecture, choose the models, build the system, integrate it with your tools and take it all the way to production. The goal is not a demonstration, it is a system that runs, that your teams use, and that stays maintainable over time.
Why a custom system rather than an off-the-shelf tool or a SaaS subscription?
An off-the-shelf tool covers standard needs well, but imposes its data model and integrates less easily with your specific processes, your ERP, your CMMS or your MES. A custom system starts from your reality: your data, your constraints, your business rules. It does exactly what you need, with no useless features, and you keep control of it. Custom development is justified whenever a process is specific, sensitive, or poorly covered by the market.
Why local AI rather than the cloud?
Local AI processes your data on your own infrastructure, without sending it outside. That is decisive when the data describes processes, defects or information covered by industrial secrecy or contractual clauses. We design local, hybrid and private-cloud systems alike. The choice is made during scoping, according to your sovereignty, latency and cost requirements, with your IT department involved from the start.
How does a project run, from idea to production?
We follow eight steps: discovery, business analysis, architecture, prototype, development, validation, deployment and evolution. Discovery frames the decision to improve. The prototype proves feasibility on your real data before any heavy development. Going into production and adoption by your teams are planned from the start, not handled at the end.
How long does a first system in production take?
It depends on the scope. A prototype usable on your data usually takes a few weeks to build. A first system in production on a narrow scope is measured in weeks to a few months. We favour a tight first project, put into service quickly and then extended, rather than a large project that produces nothing usable for a long time.
Who owns the code and the data?
Your data belongs to you and is used only for your project. For the code, we agree on the ownership and licensing model at the outset, including handover of the source code when you want it. The goal is that you are not locked in to a vendor: a system you can extend, take over or hand to a third party if needed.
What results can you expect from a custom AI system?
A well-targeted system saves time on a specific task, makes a decision more reliable, and turns dormant information into something usable. Results are judged on a concrete deliverable and a decision to improve, defined during scoping, not on a general promise. If the first scope meets its objectives, you extend it; if not, you adjust, at the cost of a limited scope.
An industrial challenge to tackle with AI?
Tell us about your need. A first conversation is enough to gauge whether a custom system fits and decide where to start.
Book a call