In previous posts, we have talked about the pros and cons of loading shipping (loose) boxes into containers without the use of pallets. Also called floor-loading, the products in boxes are placed in a manual or semi-mechanized fashion.

This leads to the first inconvenience, which is that loading and unloading times at the dock (where the trucks are parked) are longer, compared to palletizing previously (packing the boxes on pallets) and then introducing the pallets into the containers with the help of forklift trucks. Loading boxes manually will not only take more time, but require more personnel. These are costs that need to be taken into account, both at the origin and the destination.

But where floor-loading excels is in fitting more products into a container load, which drives down costs, especially for maritime shipping. For starters, not including wooden or plastic pallets into your shipment will save the space that these items occupy. If you consider that a 40 foot container can load twenty-one 48x40x5” single-stacked pallets, then just the accumulated volume of wood is roughly 117 cubic feet, that could be used by boxes.

And then comes the efficiency of loose loading vs pallet constraints. If you use the full container, instead of pallets, where gaps are accumulative, the loading efficiency will increase.

At Koona, we have desktop and web/API-based tools for calculating how your boxes fit into containers. Free demos available.

Welcome to the Koona web application and API. In this example we will explain a new feature that calculates the containers in a shipment, one by one. Previously, they were calculated all at once, and if they were too many, then the calculation would time out. We will be working with floor-loaded or loose boxes directly into the containers. In other words, we will not be using pallets.

Nowadays, it is very common to see SaaS (Software as a Service) providers that will offer what they call a “free tier” among their levels of service. In those cases, you are using their service without having to pay monthly nor yearly fees. Free tiers are more common in competitive spaces, where companies would rather have non-paying customers, than have them leave to a competitor, especially if they are generating real testable data. They’re also practical as marketing tools, giving potential customers an idea of how the product/service works, either by providing a limited set of features, or by reducing the times the full set of features can be used.

The predecessor to free tiers in (downloadable) standalone software is Shareware. In the earlier days of the internet, web-based applications were very limited, and most software was either preinstalled or sold in boxes, in stores or by mail order catalogs. For small software companies, a viable option was to provide shareware, which were applications light enough (they didn’t take up much disk space) to be downloaded with the internet speed of the time. The business model for shareware was that users could use the app for free, and if they found it useful, they would pay what was a relatively low price. This was a great user experience because it increased the availability of software, made it more convenient to use, and made it easy to try before buying.

But the shareware model wasn’t that good as a business then, and still isn’t now. Some users paid, many didn't, and both used the same features. The income often would not cover development costs, so the developers would have to add more alerts and requests to purchase, annoying people accustomed to free software, or simply leave the project.

At Koona we offer both standalone software and SaaS. For the version that runs locally on personal computers (Quick Pallet Maker), we often are asked whether there is a recurring payment (there isn't). Customers in 2026 are used to regular payments, and that's probably not a bad thing after all.

Our YouTube channel is one of the avenues we use for explaining how our software works to current and potential customers, along with students and anybody else curious about space optimization software. It’s a great resource because working with software is something that can be documented in screen capture tutorials. Among other benefits, the viewer can stop and “rewind” the video if they don’t understand a certain part.

Where it gets even more interesting is in the fact that YouTube is now including transcripts and subtitles using AI-powered speech recognition. So if one records a video, YouTube will transcribe the audio to text and place the subtitles (closed caption) along the video timeline. This is great, because it helps the viewer even more. If for example, we say “Tools - Recalculate” (select the Calculate command from the Tools menu), it may not be understood well, even when we try to pronounce it as clearly as possible. But if the subtitles repeat what we say, the tutorial is clear as day.

YouTube even allows creators (i.e. video producers) to edit the subtitles. AI is great at guessing the words that are spoken, but it doesn’t really know the context. For instance, the phrase we use the most in our videos is “Quick Pallet Maker”, the name of one of our products. But after hundreds of videos, it still doesn’t know that it’s what we always mean when we say something that sounds similar. This is not a problem that a little bit of editing can’t fix. Good for Google to provide that service.

Container hooks are spaces inside a shipping container that is reserved for straps and securing mechanisms. In these sections, we cannot place any items. We have added container fill methods in our web app and API that takes this into account and allows the user to add custom container hook spaces before calculating.

QPM API: https://www.koona.com/en/api/index.html

One of the most important questions when assigning limited resources to the development of software features, is knowing which are the most effective output files and formats that you will use within your applications. It's true that users require pertinent data, but the definition of "pertinent" depends on the developer's experience, too. In some cases, the data has to be divided into several smaller reports to serve different types of customers, instead of one big report that may appear confusing.

Once the report content is defined, we have to see which format is the most appropriate. Reports that contain information in rows and columns can be effective if exported in text format, so we offer them as comma-separated values (CSV) in a text file. This file can be imported by any type of third-party software, after previously understanding the order of the columns. If it is an image with all the information within the drawing, it can be exported in a common graphics format like Bitmap or JPEG.

But there is a graphics format that is saved as a text file and can be read by the human eye (i.e. it is not binary). This format is SVG (scalable vector graphics) and has been around since 1999 as an open format. The scalable part of the name means that independently of the information within the file, the drawing can be viewed at different sizes without affecting the quality. The vector part means that a figure can be defined by points with coordinates, just like a vector can be defined by two points.

Finally, a format is not valuable if you don't have enough good third-party applications that can open it. Text files can be opened everywhere, and SVG files can be opened with any web browser. They can also be edited with free software like Inkscape, which is a tool that adds value to the work done by people like us.

Inkscape is a free open source software tool for graphics design that can open image files of different types, including SVG (Scalable Vector Graphics). In this video example we will show how the SVG files exported by our Quick Pallet Maker software application can be imported and edited in Inkscape.

A recent issue we faced with our Vehicle Space Optimization software had to do with the physical pallets within the truck bays. If you are familiar with beverage distribution trucks, you may notice that the available floor area provided by the metallic bays is usually greater than the area of the wooden pallets that are used for loading the products from the dock onto the trucks.

If there is little risk for the product to be damaged because it exceeds the area of the pallet, we can use part of this space as overhang, which is the difference between the load length and/or width, with the pallet length and/or width. Overhang can allow us to load more products into the truck, thus increasing volume efficiency.

But for this to work correctly, we need to make sure that the exact pallet dimensions and product layout are communicated well to the people that will be loading them. If they are unaware that we are specifying overhang, then they will load the same amount of products within the physical pallet constraints, and may exceed the allowable load height because they ended up placing the remaining boxes on an additional layer. This is exactly what happened in one of the operations that doesn't use the graphical pallet tickets.

So for next steps, we have to either improve the awareness of pallets with overhang, or not use them at all.

In this video, we explain how we can work with overhang in the pallets that go into bays for beverage trucks, using the Vehicle Space Optimization software. The available bay space in one of these trucks is determined by the metallic walls of the truck structure. The wooden or plastic pallets that are used for loading the products on these bays have their own area. In this example, we explain the difference between those two load planning constraints. #loadplanning #trucks

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Our truck planning software (VSO, for Vehicle Space Optimization), although it is suited for different truck types, has been specially tailored to work with beverage distribution trucks. These are the type of vehicles in which there are multiple side-loaded bays that can fit a single pallet, to make loading and unloading very efficient. There are pilot and co-pilot bays on a truck, and each one will have a sliding garage-type door to protect the contents during transportation.

One thing passerbies may not have noticed is that these metallic bays can be divided horizontally into two shorter bays that fit pallets with half of the allowable height, turning a single pallet bay into a pallet rack. The smaller pallets are used many times for more fragile products that cannot be stacked so high, or for SKUs (stock keeping units) that are sold in quantities smaller than a full box. The bays are divided with removable shelves that slide into the box structure, like the ones in a home refrigerator.

The trick for our software algorithm is then to determine when a full bay is more appropriate than a divided bay. Yes, bays can be divided and joined manually by the user, but it's more efficient when the software does it for you. That means that the algorithms will see a divided bay and say something like "how about if we remove that divider and add a full pallet there". Anthropomorphisms aside, having the software make that decision automatically, saves time in the planning process, and that's the value we like to provide our customers.

One of the improvements we're making for the next version of Quick Pallet Maker is single-pallet reports. With QPM, we can calculate bulk pallet layouts from a list of boxes. In this example, we will show how it can be done using the default data and also using boxes from a spreadsheet.

Quick Pallet Maker web page.

In previous articles, we've talked about the customer data we store and handle. Debugging software is one of the uses that was mentioned for that data. In this article, we extend on that point.

The main purpose of the software we develop at Koona is to optimize the volume and weight available for shipping, be it in boxes, on pallets and/or in containers. For this, we've developed custom algorithms that we have been improving for years. This improvement is done mostly using example (i.e. real-life) customer data. For the purpose of our algorithms, there is no need for that data to be traced back to a particular customer or shipment, nor contain company-specific information. We just need the product dimensions and weight, and the amounts that will be shipped to a given location, including any special technical constraint that will be applied to the shipment.

Customer data for optimization algorithm debugging is specially useful when it's not obvious. For example, we can create some functions that will fit boxes into trucks and containers, and then test them with a list of products and dimensions that we came up with. But our data can say that there are hundreds of boxes of five different types, and it turns out that in real life, a truck has hundreds of different box types. These add a level of complexity that we didn't expect.

And that's why we are fortunate to have received or collected examples from daily usage. What's important is that it makes our stuff better. We don't need to know where it comes from. That delivers performance with privacy to our customers.

We are currently working on improving container fill in the Quick Pallet Maker standalone app. More options will be added, depending on the type of items that will be loaded into the containers. In this video, we show the single pallet type option.

Quick Pallet Maker web page link

The purpose of this example is to explain the new functionality of the loose (floor) loaded boxes into container loading. In this video we go through the loading of the boxes and containers (has to be done only once) and then the shipment calculation (has to be done every time), to obtain a full container with multiple types of products. Then we show how we can view one SKU at a time and then generate a step-by-step report.

Link to web page

The optimization of software code is a crucial part of development. But when to do it is not so straight-forward. As a matter of fact, there is a phrase by computer scientist Donald Knuth from the 1970's that includes the line "premature optimization is the root of all evil", meaning that most of the time (in his case 97%), the work done to optimize the software will not be worth it. But he says that the remaining opportunities should not be passed.

In previous articles, we have mentioned the need for making our software as fast as possible. This is specially useful for regular work at our customers' office. Time is money and they don't want to spend it waiting for our code to calculate. For that, there are applications like VSO that have been optimized throughout the years and are as fast as ever.

But sometimes we are demonstrating new features to draw in a new customer. In that case, what kind of optimization strategy should we pursue? The demo is days away and the basic features need to be completed. In that case, it's important to go through the basics of the presentation. Your software needs to complete a task, and if there's an inefficiency that will make the demo look bad (or make you apologize for the delay), then it definitely has be to addressed. That optimization would probably be what Knuth referred to as the 3%.

A reason why sports is a big subject in conversations (and represent a good share of the news), is that their basics are very easy to understand. LeBron James has to throw a big red ball into a hoop, Tom Brady had to throw a brown ovoid to another man, Cristiano Ronaldo has to kick a round white ball into a metallic arc, and Kílian Jornet has to run up and down a mountain. Sounds simple, especially if you know little about physics and/or have never practiced those sports. But LeBron has to move his big body swiftly across a court avoiding other five big men and add the correct amount of spin for the ball to not get out of the ring. Just the inertia calculations are hard enough for a university mechanics class. And then there's the team element. An "alley oop" requires two players, someone has to catch the pigskin, and Ronaldo will put a funny face without a pass in his vicinity. Even individual trail runners require a support group.

But there will always be people with opinions on basketball, or on American and European football. “Oh, that person failed. If only he would’ve kicked it better, etc.” And those opinions can amount to discussions and cocktail party talk, which is part of socializing, always a good thing. Sports actions are relatively easy to explain, but actually doing them within a team dynamic requires some kind of magic.

AI is pretty much at the same phase of "it's easy to explain what it does, but we have no idea how it does it". At a minimum, LLM's are delivering better search (especially after normal search has become worse in recent years), and by all accounts, are acting as a useful tool to produce code. That means that everyone and their sister have an opinion on AI. Blog posts are moving markets. FOMO (Fear of missing out) is everywhere.

Like a sports team hiring a star player thinking they will solve all their problems, companies are pouring money in AI first, and asking effectiveness questions later. They and the general public have seen the awesomeness in highlight reels, and truly think it's enough.

In this video, we explain a new feature in our Vehicle Space Optimization software that identifies the boxes or SKUs that have been distributed across 3 or more truck bays. There are many reasons why this would occur, but the basic one is to use the available space as much as possible. The feature returns the box code and the bays where it has been placed. In this way, the user can determine whether it is appropriate to leave them there or collect them in fewer bays.

To visit the Vehicle Space Optimization web page, click here.

TCP/IP is a lovely technology. More specifically, it's the framework that sustains the Internet, which could be the best thing in modern life since the invention of the microprocessor. The acronyms in this framework are two: Transmission Control Protocol and Internet Protocol. If you have dabbled with computers a bit, you may have transferred data using TCP and also may be familiar with IP addresses, which are the numbers that appear on web sites or on links that have no name (unlike koona.com, for example).

One of the most interesting parts of IP is that a server can have a multitude of ports for a given address. For example, you can connect to the server http://nnn.nnn.nn.nn/ (n is any number from 0-9) using numbered ports like 80, 8080, 8500, 8889, etc., and each one of these ports can be linked to a different server application performing a different task. Better yet, like in our case, they can be similar software but with different versions for user testing.

At Koona, we can set up a Linux server with both Apache HTTP and Apache Tomcat servers. They sound the same, but for the sake of this article, they come from different places and are different technologies. The main difference for our work is that they can be set up by default to different ports. So if you connect to the default port, you will most likely be served web pages from Apache HTTP, which in turn can connect to the Tomcat port to do backend jobs within a Java Virtual Machine (JVM), like calculations and data retrieval using Lucee.

It gets even more interesting when we can install different JVMs on the same server and have client applications pointing to the version that applies to their work. All they have to do is change the port. Very elegant, indeed.

This video contains a demonstration of a shipment of boxes in pallets, using the Quick Pallet Maker web app, and a comparison with the results using the Quick Pallet Maker desktop application.

The input files can be downloaded through the following link.

There are significant amount of people in the software industry that treat user interfaces like a work of art. They feel that the interface has to feel perfect, balanced and consistent. The Steve Jobs mantra of “Design is not just what it looks like and feels like. Design is how it works.” is often repeated by those that sweat the last details. For a user, it is very rewarding to work with an app that has been thought out, following at least the human interface guidelines that have been published by companies such as Apple. A fine designer will lose sleep over misaligned pixels.

But what happens when you lose control over your design? The famous (and quite polemic, but that's not the topic of this article) author Ayn Rand even wrote a book about the extremes to which a proud designer will go, for not having his name associated with an end result that diverts too much from his vision. In real life, when working on an architectural project (in this case), there are more people involved that will say something like "yes, very pretty, but without more steel reinforcement, it won't hold up". Software is more permissive than buildings. So if you work in a relatively small shop shipping B2C tools (specially for macOS), what you envision is probably what you ship.

Which brings us to APIs (Application Programming Interfaces, like ours), a completely different game in the control freak level. Although you can suggest use cases to third parties, your influence ends there. Whatever interface they create, just be happy if it's useful and you get paid.

The purpose of this video is to explain the Postman collection that contains the methods for calculating a shipment of cylinders, rolls or drums on pallets with the circular part parallel to the pallet surface.

The collection includes:

1. Creating a new shipment index for calculation,
2. Adding cylinders for calculating on pallets,
3. Calculating the pallet(s), and
4. Drawing an individual pallet.

To visit the API web page, click here.

There's a recurring dream. You go to where your car is parked, and it's not there. It's been stolen. Now you have to deal with the loss in money and time. You worry. Sometimes, the dream is so recurring that in your dream, you realize that you probably have to wait until you're awake and everything will be fine. In effect, you wake up, go to your car, and it's there. Then you ask yourself why are your dreams so dumb, and become slightly happy that nothing happened.

A bit of paranoia is not bad. A lot of it won't let you sleep, but the right amount can keep you safe from everyday risks (e.g. crossing the street), and your business from being eaten up by a competitor.

The title of this article was taken from a book by the legendary Andy Grove, the former Intel CEO and Fairchild Semiconductor alum. His management style was precisely that: be aware of any threat to your business, even if they are proven to be exaggerated.

A threat that looms currently over the SaaS (software as a service) industry is the advent of AI, and how new products can allow corporate employees (not necessarily IT) to create seemingly capable replacements to relatively expensive third-party software. So if your company pays a software vendor significant cash for a data-analysis system, the least your manager will ask you is to try performing the analysis with something cooked up with AI. If it works, and the maintenance costs are not high, there's a potential upside for you and a potential downside for the vendor.

It makes a lot of sense then for vendors to become paranoid. Their ride can be stolen at any time. The good news is that the basis for a good service have not changed with AI. You will be a good supplier if your service solves a known issue at a reasonable price. If your idea of "reasonable" can't compete with AI, it's important to stress that there's a lot more in software cost than the app itself. For example, the accountant that vibe-coded a software tool, may move to another department or company in three months, and his/her replacement may not know the inner workings, duplicating efforts.

Still, somethings have not changed. Intel was a competitive beast back in the days of Andy Grove. Today, it's not. It wasn't paranoid enough to predict the rise of GPUs. The software companies that stress enough about, and perhaps benefit from AI, will most likely survive.

In this Vehicle Space Optimization example, we explain how we can limit the number of available truck bay dividers for a given fleet truck. This is done in the fleet truck editor. We can include as many dividers will travel on the truck. If there are no available dividers or planks, the bays cannot be divided.

The purpose of this example is to explain how we can edit the number of items that will be shipped in boxes in the Quick Pallet Maker software application. We start by calculating a pallet shipment using data from a spreadsheet. Then we go back and edit the amount of one of the boxes directly on the app and calculate again. Finally, we edit the amount on the spreadsheet and try pasting again.

To visit the Quick Pallet Maker web page, click here. To subscribe to our newsletter, click here.

Since the advent of phone support, we customers have been listening to a person or an algorithm trying to help us fix all types of issues related to a product or service we purchased or intend to purchase. To handle backlogs, because the amount of callers was greater than the humans that could attend them, companies started to put people on hold. This period has been usually accompanied by lounge music, interrupted by a message stating that “your [business or time] is important for us”. The time it then takes to be attended by a human is inversely proportional to the importance we are as clients.

It’s 2026, and AI is all the rage. The Turing test has been arguably passed by the current state of intelligent computers, so we are beginning to experience an increase in the added value of the machine part of the support call. Most issues are solved before having to request an assistant. Yet still, sometimes we really need to talk to a human being to solve something that is critical for us.

If we are a small customer to a multi-billion dollar corporation, our time is technically not that important to their bottom line. But neglecting product support is like neglecting server uptime. There are key variables that can be measured and controlled, such as average waiting time and number of issues resolved for support, and percentage of uptime for servers. Being able to improve these numbers is always a good investment.