Use cases

Examples of what we have built

Each example describes the situation a customer came to us with, and what we built for them. Each shows both the starting point and the result.

Theme 1

Data and reporting

Bringing scattered data together into something decisions can be made from.

Merging data out of Excel

Starting point

The data was kept in many separate spreadsheets across the company. Every file had a different structure and formatting, which made quick analysis impossible. Getting the overall picture meant hours of manual merging and a constant risk of error.

Built in our application

The application merged all the data into one central database. Its interface guides users clearly to enter information in a single format. Everyone can then be sure they are working with the right data, and the basis for a decision is a few clicks away.

Consolidating data for management reports

Starting point

Management needed a quick view of results, but the data sat in several different accounting systems, one per region. Getting the whole picture meant manual exports and complicated merging in Excel. The process was slow, and by the time the reports were finished they were out of date.

Built in our application

The application pulls data from all the regional systems into a single central store by itself. It converts the differing structures into one format and prepares clear management reports from them. Management therefore has current, reliable data for strategic decisions at any moment.

Business intelligence for planning and reporting

Starting point

Company plans were built in separate, incompatible spreadsheets. Consolidating them and then comparing plan against actuals was extremely laborious. There was no single view of the data and no way to analyse deviations quickly.

Built in our application

We implemented a BI system that unified and automated the whole planning process. Managers enter plans in a structured environment and the system compares them with real results automatically. Interactive reports make it possible to analyse performance immediately and make better decisions.

Theme 2

Automation and integration

Moving data between systems without manual work and without mistakes.

Automated data import

Starting point

Users spent their time repeatedly downloading data from an external system by hand. The data also arrived in the wrong format and needed lengthy manual cleaning and editing before every use, which increased the risk of error.

Built in our application

The application connected to the external system and imports the data fully automatically at regular intervals. During the import it cleans the data, converts it into the required structure and prepares it for immediate use.

Connecting to external data for further processing

Starting point

Estate agents had to enter every new listing into the central property server and into the internal system as well. The process was slow, prone to typos, and delayed publication of the listing for no reason.

Built in our application

The application is connected directly to the central property system and imports newly entered listings automatically, adapting them for publication on the company's own property website. It formats the imported data automatically, saving agents hours of work and getting listings published immediately.

Theme 3

Operations and people

Running the everyday work — jobs, qualifications, requests.

Real-time tracking of vehicles and cargo

Starting point

Dispatchers had no immediate view of where vehicles were. To find out the state of an order and the estimated delivery time they had to phone drivers repeatedly, which was inefficient and held both sides up.

Built in our application

We extended the logistics system with a module that reads data from several GPS providers. Dispatchers now see the position of every vehicle in real time. They have a complete view of each transport, can keep clients informed proactively and plan better.

Central management of staff qualifications

Starting point

Records of qualifications and training were spread across Excel files. It was hard to plan staff development, keep an eye on certificate validity, and check quickly whether a team held the competences a new job required.

Built in our application

The application centralises all information about qualifications. For each position it defines the skills required and compares the plan against reality automatically. The system watches the deadlines itself, identifies training needs, and gives HR and managers a complete view.

Managing IT requests effectively (ServiceDesk)

Starting point

Requests to the IT department arrived chaotically, by e-mail and by phone. There was no central record, and no clarity on what was being worked on or at what priority. Users also had no feedback on the state of their own request.

Built in our application

We deployed a ServiceDesk application that serves as the single point for entering every IT request. Each ticket is logged automatically, given a priority and assigned to a resolver. The whole process is transparent both for the IT team and for the users, who see the state of their request online.

Interactive information system

Starting point

Receiving and coordinating service requests was disorganised. There was no single system for recording them and then handling them smoothly, which led to downtime and confusion.

Built in our application

We built an application that takes requests through an online form. The customer is kept informed from the moment the request is entered through to it being handled, and is then directed correctly and in time to final collection by information screens at the service point. Alongside far more efficient handling of requests, customer satisfaction with the service process rose sharply.

Theme 4

Artificial intelligence

AI that sees into company data and works inside it — not one that only answers over a general model.

An AI assistant that also writes to the data

Starting point

Finding what you need in the system means going through several screens and filters. The assistants people know from a browser window will answer, but they cannot see company data — and cannot change anything in it. So the manual work stays: find it, retype it, save it.

Built in our application

The assistant is connected to the real data in the application and can not only read it but change it — fill in a form field and save the form, edit a table row, run an action. Writes go the same way as manual work, so all the validation and every permission of the signed-in user still apply. Above the general tools sit the domain ones: in a maintenance application it finds a machine and assembles its hierarchy, shows open faults or the state of the stock. Wherever there is a text field there is a microphone beside it — dictated text is transcribed including the technical names of machines.

AI that picks the right person

Starting point

Deciding who should take which task is a manager's daily work — and it is done from memory. Who holds which qualification, who is on shift right now and who is on call is held together only in their head. With more people and more machines, an oversight becomes unavoidable.

Built in our application

The application keeps a matrix of worker skills along with their shifts and on-call duty. From that, the assistant builds an order of suitable people for a specific task: it scores them by qualification level and adds a bonus depending on whether the person is currently present, scheduled or on call. It returns a ranked list with the reasoning — so it is visible why each person was put forward.

The company AI gateway, under control

Starting point

When a company starts using AI, accounts, keys and invoices multiply. Nobody really knows who sent what, what it cost, or whether sensitive data went with it. And when a better model appears, the integration has to be rewritten.

Built in our application

All communication with AI goes through one gateway. Request categories are routed to a suitable model automatically, and there are eight providers — they can be changed without touching code, so no dependency on any one of them arises. Before anything is sent to the cloud, the text passes a sensitive-data check. Every request, answer, token spend, cost and latency is logged, and budgets are set per user and per team.

Do you recognise yourself in any of these?

Write to us about what you need to solve. We will talk through, with no obligation, whether the platform is right for you.

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