The business world is becoming increasingly digital. However, independence is important – as is profitability. If you want to digitise, you have an important decision to make: do you prefer to develop a software solution yourself or buy it from an external provider?

Both have advantages and disadvantages. This blog article explains what you need to consider. In the lower half of the blog article, we look specifically at what can lead to challenges when developing AI solutions for companies.

Advantages and disadvantages of standard and customised software

In the first part of this blog article, we would like to look at the “standard arguments” for and against the respective solution options.

Advantages and disadvantages of standard software (buy decision)

Standard software is a software system that can be purchased without major customisation. Standard software usually offers various options for customisation through configuration, but only limited adjustments are usually made. Standard software is usually developed by software manufacturers.

Availability – the software solution usually already exists and can therefore be used quicklyComplexity – software solutions that have been developed over many years can offer more functions than are required for a specific use case
Development risk – no development risk, as there is no need to budget for extra expertise/resourcesDependency – if the provider gets into difficulties or increases prices, this has consequences for the customer
Calculability – prices are clear from the outset and there are no unexpected problems for companiesIntegration capabilities – not all required interfaces may be offered
Maturity – Standard solutions are generally mature products without “teething troubles” and proven use casesLicence costs – Even if the costs are calculable, the use of the software alone costs money
Scalability – Standard software is usually easily scalableUpdating – When it comes to technological developments, you are dependent on the speed of the technology provider.

Of course, the list can be extended to include, for example, advantages through standard interfaces, proven market performance, consulting or documentation.

Advantages and disadvantages of customised software (make decision)

Customised software, on the other hand, is developed by IT service providers, consultants or by the companies themselves specifically to meet the needs of the company using it 100%.

Competitive advantage – The software solution can be developed according to your own requirements and thus generate a real competitive advantage that cannot simply be imitated by the competitionDevelopment costs – Development requires a lot of expertise and capital. Under certain circumstances, unforeseen events can cause costs to rise uncontrollably.
Independence – Companies can act independently of providersTime – Software that has yet to be developed cannot be used immediately, which means disadvantages
Integration compatibility – Companies are in control of the interfaces and can define them as required.Documentation – If you don’t have good documentation, you are dependent on the people who developed the software to make changes in the future
Customisability – Where required, the software can be customised according to individual needs.Risk – As experience is not built up over years or the software cannot be optimised across various customers, there is a risk of failure
Usage costs – There are no licence costs for the use itselfIntegration problems – Software solutions that have to be integrated with many different systems can lead to problems with interface maintenance in particular

Of course, there are further advantages here too, such as full ownership of the rights to the software and full control over what happens to the data.

Times are changing…

The business field is becoming more and more complicated these days. It is becoming more difficult to find people with the right expertise and at the same time you are losing focus on the day-to-day business. In addition, employees’ expectations of software are also increasing. In essence, of course, it is always important to define the right use cases as a first step.

The points mentioned so far are at a relatively high level. In our view, what is much more important are further points that will become increasingly relevant in the future:

User experience (UX)

Users are familiar with this from their private lives, as B2C apps such as TikTok, Instagram and the like demonstrate: Software is child’s play to use and doesn’t require much training. Younger employees in particular expect enterprise software to be easy to use and not require extensive training. Modern software manufacturers now have entire UX teams that focus exclusively on ensuring that the software is easy to understand and intuitive for users. Who wants to use software today that only thinks about processes and not about the user?

Data protection and IT security

IT security is becoming an increasingly important issue for companies. Any software can potentially be a gateway. It is therefore important to know the software well and to secure the potential points of attack professionally. The question is whether companies that develop customised software have sufficient expertise to secure their company with regard to IT security and increasing GDPR requirements.

AI development

Especially when you look at use cases like the ones we solve with amberSearch and amberAI, it is important to understand the complexity. AI is currently developing so rapidly that you have to be prepared to invest continuously to stay up to date. No company benefits from software that is outdated after a short time because it is not developed further – or even worse – the chosen technology can no longer be combined with the state of the art at some point.

Operation & maintenance

One part is the development of such a solution. The much larger part is operation. Interfaces, processes and requirements change. There are always issues that need to be optimised and where further added value needs to be realised. Servers have to be looked after and maintained. Can these costs be estimated accordingly?

Interfaces & API’s

To avoid having even more data silos in the company, it is important to allow the systems to talk to each other. If you develop your own software, you naturally have to develop all the interfaces yourself and cannot rely on ready-made modules.

Business case/ROI

At the end of the day, the purchase of software is a purely economic one: Does using a particular software for a particular use case make the company more efficient? If so, does it make more sense to buy or develop this solution?

When should you develop software yourself?

Of course, there are also some arguments and situations in which it makes sense to develop your own software. We have therefore listed some situations below in which it makes sense to develop your own software:

  1. Specific requirements: If the software has to fulfil very specific requirements that are not covered by existing solutions or demanded by a wide range of companies, in-house development can make sense. Standard software solutions sometimes have the challenge of not being able to fulfil all of a company’s individual needs 100%, especially when it comes to niche requirements.
  2. Competitive advantage: Developing a customised software solution can help gain a competitive advantage. If the software offers unique features or optimises processes that are strategically important to the business, or where the software developer market is not interested in developing new solutions quickly, this can lead to a major competitive advantage.
  3. Control and flexibility: By developing in-house, the company retains full control over the development process and software architecture. This allows for greater flexibility in customising and scaling the software over time to adapt to changing requirements.
  4. Long-term costs: Although the initial investment for in-house development may be higher, costs can be saved in the long term. Instead of paying licence fees for commercial software solutions, the company has the opportunity to amortise the costs of internal development and reduce them in the long term. This should be balanced against the required hosting costs, customisation, evolving technologies, etc.
  5. Security and data protection requirements: Some industries, especially sensitive ones such as finance, healthcare, critical infrastructure or government agencies, may have specific security and privacy requirements. Internal development allows for tighter control over security aspects and compliance compared to using third-party solutions where there may be data security concerns.

Make or buy decision when using generative AI software such as that from amberSearch

Of course, nowadays you can quickly put together a minimum viable product (MVP) yourself. And in most cases, you can see that the software is capable of delivering added value. But there is still a long way to go from such a pilot to a productive system. The question for companies is whether they really want to spend the money to build their own MVP if they are not prepared to invest the money to get it into production.

At amberSearch, we help companies to make the existing expertise that has accumulated over the years in various data silos available in one central location with the help of modern AI technology. For years, we have been developing our software with the full focus of a continuously growing team of developers and have learnt a number of lessons. A company that develops such software itself would first have to learn these lessons itself and then implement them.

Anyone who tries to build a solution for the use case that we solve with amberSearch should be aware that it is not that easy:


The main point will be the integrations. At amberSearch, we think of integrations in two ways. On the one hand, it is about our software being able to connect internal company data silos so that the user is able to potentially find all information. On the other hand, it is also about making the software available to the user as easily as possible. This includes, for example, the employee being able to access the software from different locations. These points must all be supported. By this we mean, for example, team apps, IFrame integrations, mobile optimisations, etc.

Access rights

Anyone who has connected the various systems must understand the access rights. If you offer your employees an AI assistant, you have to expect them to be able to find all the information they need. Do the developers in all connected systems understand the authorisation structures in depth in order to be able to cover all cases? Of course, such systems can be limited to the generally publicly available data, but it will be very difficult to explain to employees in communication why only a relatively small data set has been included in such systems.

GDPR & IT security

GDPR requirements are becoming increasingly demanding. Especially in combination with AI models, it must be ensured that data is not accidentally used differently than intended.

Customising AI models

Nowadays, the trick is no longer to develop or train an AI model yourself if you are provided with sufficient resources. The art lies in optimising the parameters of the AI models and adapting them to the use case. It takes many projects and years of experience to do this really well for a use case like ours. As the correct parameterisation of the AI models is not so easy to reproduce – although this is where the real know-how lies – we have made some of our AI models open source.

Economies of Scale

Those who rely on a solution like amberSearch have the advantage of economies of scale, as the costs of new functions are naturally shared across many customers. Investment in new functions and technologies is continuous, so that companies that invest in solutions such as amberSearch always have the most up-to-date systems.

Conclusion on the make vs buy decision for AI software

There are arguments both in favour of and against a make vs. buy decision. In increasingly complex situations, companies should not lose focus on their core business and ask themselves whether they have sufficient resources available to be able to react to imponderables and unforeseen events.

Agencies, IT service providers, consulting firms & co. They all want a slice of the AI pie and want to realise projects with their customers. The question that companies need to ask themselves is whether the use case is so individual that it cannot be covered by standard software or whether the use case is really so individual that the investment and risk are worthwhile.

Especially with the current speed of development, it is not enough to introduce the software once – it is a continuous development that constantly requires resources – in development, support or operation.

And last but not least, there should be a lot of dialogue with employees in order to take their expectations of the UX, the content (keyword: access rights) and the like into account.