About ActARion

Technology is reshaping how we live, learn and work – and the pace keeps accelerating. At the same time, many organisations struggle with the same questions:

• How do we keep up with new technology while production has to keep running?
• How do we cope with shortages of technical talent and the retirement of experienced staff?
• How do we train a new generation that learns visually, on-demand and on their own terms?
• How do we reduce downtime and errors when processes, products and regulations change faster than our documentation?

Traditional approaches – binders, PDFs, classroom training, job shadowing – are no longer enough. They are slow to update, hard to search and difficult to standardise across shifts, sites and countries. We started ActARion to address exactly this gap.

ActARion turns your operational know-how into AR-powered, step-by-step guidance that runs on smart glasses, tablets and other connected devices on the work floor.

In practice this means:

• Knowledge capture in the real environment

  Experts record procedures directly on the line or installation using smart glasses or mobile devices. No separate film crew, no long editing cycles – just real work, captured once and structured into reusable AR Standard Operating Procedures (AR-SOPs).

• Guided work instructions with AR and AI

  Operators see exactly what to do next, overlaid onto the real world: 3D cues, images and short video snippets supported by concise text, automatic translation and optional text-to-speech. This reduces cognitive load and makes complex tasks accessible for new and experienced operators alike.

• Remote expert support when it really matters

  When a breakdown occurs or a rare scenario appears, operators can call an expert who sees what they see and can annotate directly in their field of view. This underpins our remote expert support for corrective maintenance use case.

• Data for continuous improvement

  Each execution of a guide can collect evidence (photos, video, confirmations) and performance metrics such as time, error rates and completion steps. This feeds a skills matrix and helps you optimise procedures, training and maintenance strategies over time.

Our use case portfolio ranges from AR-guided assembly for error-free production and guided changeovers to reduce downtime to preventive maintenance with data-driven insights and training and onboarding for industrial teams. You can explore all use cases on the use case overview page.

Across manufacturing, logistics and processing industries we see recurring patterns:

• Corporate memory at risk

  Procedures live in the heads of a few veterans or in scattered notes and videos. When people leave, knowledge leaves with them. Our AR work instructions and SOPs to preserve corporate memory use case addresses this directly.

• Slow, inconsistent onboarding

  New hires depend on job shadowing, pulling experienced staff away from production and resulting in different ways of working per shift, line or plant. With AR training and onboarding we shorten time-to-competence and standardise learning.

• Paper and PDF instructions that do not match reality

  Work instructions are hard to maintain, not always opened and often lag behind the actual process.

• Complex changeovers and batch prep

  Setups and changeovers are time-consuming, error-prone and heavily dependent on specific people. Our guided changeover approach makes this more robust.

• Preventive and corrective maintenance under pressure

  Maintenance teams must keep uptime high while dealing with complex assets, long travel times and incomplete histories. Here, AR-guided preventive maintenance and remote expert support work hand in hand.

All of these use cases are supported by one central AR-SOP library so you can build, maintain and roll out standardised ways of working across sites and countries.

We believe in "think big, act small and show results". Instead of long programmes, we focus on concrete use cases with measurable impact.

1. Point of departure – We start with your strategic and operational questions. Where are the biggest risks? Where do errors or stoppages hurt most? Where is knowledge most fragile?
2. User insights on the work floor – We talk with operators, team leads, quality and maintenance staff to understand how work really happens today and where digital support can help instead of distract.
3. Co-create a first solution – Together we select one or two high-impact use cases – for example onboarding on a key line, a complex changeover or a high-risk maintenance procedure – and build AR-guides with your experts.
4. Pilot → impact → scale – We run a pilot, measure impact (training time, error rates, downtime, first-time-right), refine the guides and then create a roadmap to roll out to other lines, sites or countries.

This way, AR and AI are not a "shiny demo" but a practical tool that proves value in weeks, not years.

ActARion is the European partner of DeepSight, a Montreal-based AR and generative AI knowledge management platform used in industries such as mining, aerospace, agro-food, wood and metal transformation and transportation.

Together we bring:

• A mature AR & AI platform focused on work instructions, training and support.
• Experience across high-demand, safety-critical environments.
• Support for smart glasses and mobile devices, with a roadmap for modern AR headsets.
• Integration options with your existing systems for maintenance, quality, learning or production data.

We work with a growing network of local technology, integration and education partners to ensure that AR and AI connect to your reality – technically, organisationally and culturally.

ActARion was founded by experienced entrepreneurs and operators who have built and scaled digital and industrial businesses. We combine:

• A deep understanding of production, logistics and regulated environments.
• Experience in digital transformation and change management.
• A strong partnership with a specialised AR & AI technology provider.

We are not just here to sell software. We are here to help you answer questions like:

• Where does AR and AI really add value in your operations?
• How do we bring operators, engineers, quality and HR together around one way of working?
• How do we start small, learn fast and build towards a sustainable, scalable solution?

If these are questions you recognise, we would be happy to explore them with you – starting with a concrete use case from our use case library.