Make or Buy Artificial Intelligence Virtual Expert to support SOC procedure

SOC Triage Analysis: what is best between developing your software solutions or buying a ready-made AI one and integrating it into your existing workflow?

Introduction

Today, keeping Information Technologies under control in the company is a very demanding job and with a high rate of uncertainty in the results, in a few years we have gone from a determined and finite perimeter to a cloud of processes that are not always under control.?

The techniques used to identify possible attempts at compromise must necessarily integrate aids and supports without which humans alone cannot cope.

?At the same time, Cyber Crime has become an industry and as such managed, the human resources necessary for a company to defend itself are increasingly precious, rare and expensive.?

This is why traditional solutions are used alongside Artificial Intelligence processes, to reduce the number of findings that a human analyst has to verify and to automate the identification of the thousands of most common and/or well-known cases.?

Many stakeholders rightly have their IT history behind them, made up of investments to be amortized and solutions to be integrated; what can be done to add AI to what already exists??

Buy or Make?

It is a very challenging question, and it is even more engaging when it comes to the Cybersecurity ecosystem. Here, we want to explore what to consider and where pitfalls come in.

A vendor specialized in developing Artificial Intelligence instances or Virtual Experts gives a business several compelling advantages to buy an existing solution rather than attempting to create a similar system internally.

Still, potential customers should consider the potential drawbacks or challenges they might face when opting for an external solution instead of developing their own.?

By example purchasing an AI Triage Analysis solution from a specialized vendor offers advantages in terms of expertise, reliability, cost and time efficiency, support, scalability, and overall risk reduction.

These must be compared with the company’s needs, resources, and long-term strategy. Sound reasonable to compare the economic impact of significant investment and risks associated with developing an internal solution.

Development of Cybersecurity strategies and services has accelerated in the last years. For obvious reasons, criminal organizations move initial hacking challenges to an illegal industry.

As usual, Vendors' answers needed to be coordinated, and various flavors and technologies emerged to counterfeit, unwilling, or capable of collaborating between them. Moreover, IT complexity naturally exists because each company has its own needs and story; in this scenario, it will take time to consolidate and mature effective solutions.?

Artificial Intelligence processes not only support humans in their critical decisions and workflow, but they are also getting even the strategic role of better integrating different sources and data that otherwise are difficult to correlate in an adequate time.?

Besides technical and industrial pros and Cons, there are other arguments to consider that are equal to both choices but important to deal with for an adequate evaluation. The scope of this written describes some possible critical factors for an economically and successful viable option.?

Pro an AI Vendor made solution to enhance Cybersecurity workflow.

Expertise and Specialization.

Artificial Intelligence alone is insufficient expertise in an effective software cyber solution. Vendor teams have specialized knowledge and experience in robotics and automation while creating AI systems.

This often ensures the product is built on the latest research, best practices, and industry standards.?

Reduced Development Time.

Pre-built software can often be deployed faster than developing a solution from scratch.

The development process can be lengthy, delaying implementation. Purchasing a ready-made solution significantly reduces the time it takes to implement an effective system compared to the protracted process of building one from scratch.

Scalability and Performance.

A Vendor-made Artificial Intelligence system is likely designed to scale according to the needs of different organizations, accommodating growth or changes in the threat landscape without the need for significant redevelopment. It has probably been tested in multiple and various environments and has a track record of performance, reducing the risk of failure and ensuring reliability.?

Regular Updates, Improvements, Support and Training.

A vendor continuously works on improving the solution, providing updates that keep the system aligned with the latest threats and technological advancements. Ready-made solutions provide support and training, which can be crucial for the effective deployment and use of the system, which can be challenging to replicate with an in-house solution.?

Integration Capabilities.

AI Vendor solution is likely built with integration in mind, making it easier to fit within a business’s existing IT infrastructure and work seamlessly in complex environments.

Evaluation of this is possible by calculating the number of ingestible data sources supported or verifying the existence of API to integrate manifold other solutions.?

Cost Efficiency and Focused Internal Resources.

By buying an external solution, a company can focus its internal resources on its core business areas rather than diverting them to developing, maintaining, and updating a complex analytical system. Buying an existing solution often turns out to be more cost-effective, especially when considering long-term maintenance and updates. It permits us to pay and grow as needed.

Compliance and Security.

A Vendor solution will likely adhere sooner with compliance to industry standards, or in a non-mature market, like Cybersecurity still is, will drive their adoption, giving a clear positioning advantage. Homemade solutions may risk building a system that only partially adheres to coding standards and more; following the evolution of standards is a full-time job on top of development.?

Cons in an Analysis homemade choice

Cost Over Time.

Developing an internal Analysis solution requires significant research, development, testing, and maintenance investment. The initial investment might be lower than buying an AI vendor-made solution, but today, most AI solutions are sold based on subscription, and out of the initial effort in integrating them, they rely on a “pay as you grow base.” Over time, the costs of licensing, subscriptions, or service fees will follow the sales success. They are making it a more manageable option in the long run.?

More Customization, Limited Control Over Updates and Changes.

In-house solutions can be tailored more precisely to specific needs. A Vendor solution, although highly sophisticated, might align differently with every unique business process or requirement a particular customer has. Still, as customized as it will and should be, it will be challenging to keep the software functioning. Problems may arise with the size and tailoring function of unique customer requests. The timing and nature of updates or changes may severely impact core business, drawing back advantage of homemade choices.?

Response to Evolving Needs.

While you strive to keep your solutions updated, the pace and direction of updates may not consider the immense panorama an AI-specialized vendor has; being in touch with more customers and different situation always align with the evolving needs or priorities of the overall market. Your chances of introducing new features will be significantly less.?

Dependency on Vendor and Risk of Vendor Lock-in.

Customers depend on the vendor for updates, support, and future development. If the vendor discontinues the product, changes direction, or goes out of business, this could pose significant challenges.

Long-term reliance on a solution may lead to vendor lock-in, making it challenging and costly to switch to another resolution or vendor in the future.

Still, with dependency on a vendor, Open Standards, Awareness of the issue, and Cloud Computing are highly reduced today in 2023. Where API and Microservices Architecture exist, the Vendor offers more interoperability than in the past, reducing Lock risk.?

Integration Challenges.

While designed to be compatible with various systems, integration challenges can still exist with a company's existing IT infrastructure or specific tools, which could require additional time and resources to resolve.?

Data Security and Privacy Concerns.

Using an external solution involves transferring data outside the company’s internal systems, which might raise concerns regarding security, privacy, and compliance, especially in highly regulated industries.

However, the in-house solution is also challenging to manage; most Cloud providers offer a localized solution to adapt more quickly than in the past with GDPR or vertical requests. Often, data are more protected in cloud infrastructure (where proper backup policy exists).?

Potential for Feature Overload.

A home-made solution might include many features to cater to a diverse clientele. Still, not all features may be relevant to every customer, potentially complicating the user experience. Vendor solutions to buy will be less flexible but will concentrate on what most end users will request, permitting SOC or MSSP to focus on delivering high-quality services and sales.

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Learning Curve, Documentation and Knowledge.

Adopting a new external solution requires training and time for staff to become proficient, which can temporarily affect productivity. That also exists in developing internally, and the cost of maintaining updated documentation and spreading knowledge is not divided by multiple customers but relies only on the internal budget.

More Decision Considerations

Core Business Needs and Time to Market.

Speaking of AI, SOC automation means delivering quality services and evidence according to the defined SLA. A successful SOC's quality and process efficiency are often more critical in terms of “remaining on the market” than developing an owned intellectual property.?

Writing and developing software is and has to be considered valuable only on an industrial basis and as a core activity. Otherwise, there will always be a possible waste of resources and many risks of not matching the SOC quality requested to stay and grow in the market.?

Software custom development is justified only where it is very strategic. A company must decide its role in the mid and long-term. When there is a specific size market footprint that will justify developing homemade solutions, past-made choices could be reconsidered. Still, sales revenues will better support such internal decisions.?

Internal barrier and human resources

Most of those who find it challenging to consider purchasing a third-party solution have, in the past, made great efforts to develop and integrate an effective workflow.?

Nothing is more complex than changing a process people have become accustomed to working on. This is the main barrier that must be broken. Moreover, the human resources who have managed home-made development in the company and who see change as a possible moment of crisis, often also of a professional nature, which they have difficulty dealing with.

Pro and Cons Final Thoughts?

Purchasing an AI solution from a specialized vendor to make a cybersecurity workflow more effective will offers advantages in terms of expertise, reliability, cost and time efficiency, support, scalability, and overall risk reduction. Avoid defocusing from the central enterprise and the HR risks associated with developing an in-house solution.?

In the management and delivery of SOC services, internally or in the case of MSSPs to third-party customers, it is necessary to evaluate the value of the change and the future benefits that will be acquired in terms of production capacity and market positioning.?

The choice must consider the need to penetrate first and then remain in the market, albeit expansive, which will require more and more quality and effectiveness. Values that, with the sole support of adequate AI processes, will be able to deliver competitively.?

The importance of supporting the inclusion of Artificial Intelligence in support of a "core" activity such as the SOC must be managed and shared by the company's decision-makers, especially those responsible for generating revenue streams or business continuity.