Manufacturing · Enterprise systems · Applied AI
Manufacturing data and AI consulting begins with the factory’s operating reality: orders, materials, people, machines, quality and maintenance. SmaCtory connects that context with enterprise technology and data.
The founder’s background includes manufacturing and enterprise systems, discrete and project manufacturing, ERP add-ons, smart maintenance, automation and Industry 4.0 initiatives. We use that perspective to define practical improvement opportunities.
Where technology meets operations
Understand the workflow
Map the operational process and the decisions that affect delivery, quality or productivity. Identify where fragmented information, manual steps and unclear ownership create friction.
Connect the foundations
Review enterprise systems, operational data, integration, definitions and quality. Understand the data needed to connect planning with execution and operational reporting.
Prioritise useful applications
Evaluate analytics, automation and AI opportunities against data readiness, operating constraints, user needs and measurable success criteria.
Areas we can explore together
- Order-to-production workflows, planning and material readiness.
- Discrete and project manufacturing processes and ERP integration.
- Quality, maintenance and operational-exception workflows.
- Data architecture, integration, reporting and master data.
- Predictive use-case discovery, workflow automation and Industry 4.0 roadmaps.
- Product discovery and requirements for focused enterprise add-ons.
A discovery-led approach
We begin with stakeholders and an operational process. We then review the systems and information involved, define the main sources of friction, and prioritise an initial improvement scope. The result should make clear what can be improved now, what depends on better foundations, and what needs further validation.
What a starting engagement can produce
An agreed scope may include a process map, current-state assessment, operational pain-point analysis, data-readiness review, prioritised use-case backlog, integration requirements or MVP definition. Implementation responsibilities and success criteria are defined with the organisation.
The Smart Manufacturing product direction
Alongside consulting, we are exploring a configurable manufacturing workflow covering planning, materials, production, quality, maintenance and exceptions. It is a discovery concept. The first customer workflow and MVP boundary will be defined with industry users.
Common questions
Do we need to replace our ERP?
Not necessarily. Discovery should establish whether the priority is a process change, better data, integration, an add-on or a larger systems change.
Can we start with one factory workflow?
Yes. A bounded operational workflow can provide a useful starting point, with the required stakeholders, data, dependencies and success measures agreed first.
Start with the operational challenge.
Tell us where work slows down, information gets disconnected or decisions become difficult.
Discuss manufacturing data and AI →