Problem
They lacked a reliable, end-to-end view of what happens in their warehouse processes (receipts, shipments, returns, internal moves, adjustments) and how those movements should be reflected in their order data, COGS, and accounting. This has been their biggest source of "silent" financial errors.
Initial prompt
I need you to build me an app where I can create stock movements to our Selveo WMS. Here is a step-by-step guide on how the flow must be: 1) A page with a text field where I can scan a barcode. Next to the field there must be an enter button labeled: proceed. The text field itself must have an enter function also. So, if I press enter while in that field, it must trigger the same as the proceed button 2) Action when pressing enter, run this query through Selveo API to load the product attached to the barcode: <redacted> after running the query, the data must be displayed on a subpage. Display the following data in separate fields. It must be shadcn boxes and a very simple layout: ssin, name, weight, price, created_at, updated_at, sku, archived_at 3) For this data: images {url} , you must create a field which loads the image from the URL, if any URLs are present. Must be on the same subpage as the data in step 3. 4) To the right on the subpage, you must create a field where I can scan a warehouse location: Our standard for locations is: "<redacted>“. All locations scanned must follow this pattern. 5) When scanning a location that is valid, we must create a SSIN stock movement to Selveo. Here are some data from the different steps when doing it in the browser: <redacted>. Do you have any questions or are you missing something to be able to succeed with the task?
Final app
Outcome
They uncovered and monetized +250,000 DKK in products that had gone missing, or were not in the webshop. We gained dramatically better operational control and financial clarity, made warehouse pros/cons visible at process-level, improved the realism of return rates per market, and fixed long-standing challenges in calculating true COGS across multiple markets.
Problem
They needed a faster, less error-prone way to generate warehouse locations and print-ready labels, including QR codes, without relying on manual spreadsheets and fragmented steps. Creating labels for ~2000 locations takes up to 2 hours, due to slow QR generation and a workflow that starts in Excel and requires multiple manual steps.
Initial prompt
I need you to create an app for me, for generating warehouse locations and to export it to a xlsx file format. I need to be able to choose the following: 1) A zone letter A-Z 2) A row number - manual typing, but must be validated to only be 4 numbers and between 0000-9999. 3) A shelving unit number - manual typing, but must be validated to only be 4 numbers and between 0000-9999. I must be able to input several shelving unit numbers and the app will create a location set per shelving unit 4) A shelve number - can only be numbers and 00-15 5) A shelve space - can only be numbers and between 00-10 6) In the xlsx export I must have a joined location field, like the G column from the attached data. There must be a blank space on both sides of the shelving unit number 7) In the xlsx export I must have a joined barcode field, like the G column from the attached data. Does it make sense? Here is an example of the current excel structure we use. The export format must be exactly like that:<redacted>
Final app
Outcome
The same 2000-location output is now produced in under 8 minutes, while standardizing the logic, reducing errors, and making the process easy for non-technical warehouse staff to repeat consistently.
Problem
They had a fragmented, manual and inefficient proces for handling missing or broken goods and wrong prices when receiving goods. Processing the received goods was taking a lot longer than necessary and the lack of overview and integration between systems was costing money and errors.
Initial prompt
We want to build a system where employees can handle warnings coming from multiple systems.
Final app
Outcome
This app is already saving them 12 hours every week, and has found errors to the amount of more than DKK 100,000. This is all due to the improved continued overview it provides to employees handling goods reception, in the form of assigning problems to individual employees and tracking the status of a problem.
Problem
Their warehouse employees had a manual and inefficient process for receiving goods. It was difficult to compare the order with what was received, it was time consuming to count and scan the goods, and to register where the goods are placed in the warehouse.
Initial prompt
I would like to build a purchase order system for a warehouse. The system must be able to received products from purchase orders on a location. It must function as follows: 1. Scan a purchase order or select it from a list 2. Create a new reception for the purchase order 3. Show a screen with all products on the purchase order 4. Scan product barcode to select it or click on the product in a list 5. Select the quantity you want to move to the new location 6. Scan the location the product must be placed on 6a. If the moved quantity is lower than the actual quantity on the purchase order then show an alert and ask the user to confirm 7. Return to the productlist screen and prepare for the next scan or product selection
Final app
Outcome
Deploying this new all-in-one app for receiving goods is saving them 25 hours per week every week in increased efficiency. On top of this it creates a better overview, and it helps in the later processes of handling errors such as too many, too few or broken items.
Problem
They were struggling to translate the forecast for their campaign plan into accurate purchase orders matching in volume the expected extra sale across all suppliers. This was done in one big spreadsheet, that no one had the full overview over and where everything was done through manual copy and paste with ample room for errors.
Initial prompt
I want to build a system to extract data from a google sheet and create a range of csv files from that google sheet.
Final app
Outcome
Having converted their original spreadsheet into an app is now saving them 30+ hours during every campaign period. That time is saved because the app does it all in one place: The app check for errors, such as empty fields, dublicates and formatting errors in the campaign forecast file, then optimizes the needed amount of goods for whole colli based on expected sales, and finally splits it out based on suppliers and generates an import file for their WMS.
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A comparable Power Bi project would have cost DKK 2 - 300,000 + licenses. And on top we save ½ - 1 day every month in reporting too."
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In only 2 weeks we have developed and deployed a finance controlling tool that we've been missing for years. Before Henosia it would have been a DKK 100k months long external project."
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We have for instance deployed a keyword tool that has provided overview and a more stable workflow in daily operations. Because of this, Henosia will be a central element in our setup going forward."
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I didn't expect to use it much myself, but now I'm often vibe-coding to prototype features. It lets me test ideas together with stakeholders, directly in the product, and turn them into interactive specifications we can build from."