AI Solutions

Most businesses can see the potential of AI, but far fewer know where to begin. Off-the-shelf tools handle general tasks well, while the problems that matter most in each industry — inspecting quality, forecasting demand, processing documents — are tied to your own data and processes. Many initiatives stall at the pilot stage because the data isn’t ready, integration is hard, or the real value is never measured.

VPLUS AI Solutions partners with you across a five-step journey: assessment and consulting, solution design, implementation and integration, training and handover, measurement and optimisation. Solutions combine chatbots, document processing, computer vision, data analytics, process automation and marketing AI, or are built from scratch for your needs. Built on the VPLUS platform, they deploy faster, scale flexibly and connect with the systems you already use.

System overview

Every AI Solutions engagement follows a clear delivery process, broken into phases with defined goals and outcomes. You always know where the project stands and what comes next.

1. Discovery: work with your business teams to analyse processes, identify AI opportunities and agree on expected value.
2. Data assessment and preparation: review available data sources; collect, clean and label data where needed.
3. Proof of concept: build a first model on a limited scope and review its accuracy with you before scaling.
4. Integration: connect the model to existing systems such as ERP, line-of-business software or field devices.
5. Production: roll out the solution, train users and hand over operating procedures.
6. Monitoring and improvement: track model performance, retrain as data shifts and extend to new problems.

Key capabilities

Problem framing

Successful AI starts with the right question. The VPLUS team works with you to pinpoint the bottleneck worth solving, decide whether AI is the right tool, and define how success will be measured. This keeps resources focused on problems with clear impact, rather than adopting AI for its own sake.

Data preparation

Data is the foundation of every model. We help collect, clean, standardise and label data, and help you set up sustainable ways to store and refresh it. Well-organised data makes models not only more accurate but also easier to improve over time.

Computer vision

Computer vision lets machines see and understand images: spotting defects on a production line, recognising objects, counting goods or monitoring areas. For camera analytics in stores and points of sale, see also Camera AI.

Language processing

Much of a company's knowledge lives in text — contracts, invoices, applications, emails. Language processing extracts information from documents, classifies and summarises content, and cuts down on manual data entry. To build a Q&A assistant over internal knowledge, combine it with AI Assistant.

Forecasting and optimisation

Forecasting models learn from historical data to estimate demand, sales trends or when equipment will need maintenance. Paired with optimisation, they give you a stronger basis for planning purchasing, production and resource allocation.

Every model comes with a performance dashboard, so you can see its accuracy and the value it delivers over time.

Flexible deployment

Every business has its own infrastructure and data requirements. Solutions can run in the cloud, on your own servers (on-premise) or on edge devices close to where data is generated — ideal when processing must happen on site or connectivity is limited.

Business benefits

• The right problem, the right value: focus on issues with clear operational and commercial impact.
• Lower investment risk: prove value on a small scope with clear criteria before scaling.
• Faster delivery: build on the existing capabilities of the VPLUS platform instead of starting from scratch.
• Seamless integration: connect to current systems without overhauling every process.
• Transparent progress: every phase has concrete deliverables and tracked metrics.
• Continuous improvement: models are monitored and updated as data and needs evolve.

Use cases

Manufacturing

A factory wants to rely less on manual inspection at the end of the line. A computer vision system is installed on the line to flag defective products, running on edge devices for instant on-site response. In parallel, machine operating data feeds a predictive maintenance model, so maintenance can be planned ahead rather than handled as a surprise.

Retail and distribution

A distributor keeps running out of stock at some outlets while overstocking others. A demand forecasting model built on historical sales data is integrated with the ERP to recommend replenishment plans, and refreshed regularly to keep up with market shifts.

Finance and services

A service provider handles a large volume of paperwork every day. Language processing automatically extracts information from documents and routes each file, while an anomaly detection model flags transactions that deserve a closer look — letting staff focus on the cases that truly need their expertise.

Deployment & security

Your data is a critical asset, so deployment and security choices are agreed during discovery. You decide where data is stored and processed, in line with your internal policies.

• Deploy in the cloud, on-premise or at the edge.
• Data access scope is defined clearly for each project phase.
• Role-based permissions for users and administrators.
• Integration with existing systems through controlled interfaces.
• Handover, operations and model update procedures agreed in writing.

Alongside the solution, you can build your team's capability through AI Academy programmes.

Try it on the real system

Have a problem you'd like to test with AI? Register a trial account to explore the capabilities of the VPLUS platform on the real system, then shape the right solution for your business together with our team.