Drive Resource Studio

05/02/2026

Addressing the limitations of AI are crucial for its successful integration into engineering and manufacturing.

In our previous post we discussed the limitations of AI in an engineering context https://lnkd.in/eZu63tT7 and in this post we will explore the impact that combining with Orchestration has on AI’s positive upside potentiality.
Orchestration and AI, allows the perfect blend of the freedom of AI, but within systematic, flow-based architecture. Orchestration provides the ability to seamlessly switch between process automation, multi agent AI and human tasks. which is perfect for engineering as we move between automated digital tasks and physical production tasks constantly.

So how does Orchestration tackle the limitations discussed in our previous post?

Reduce efficacy in closed systems – defines boundaries and clearly see what is and is not being considered.

Generalisation bias – defines the information access of the AI based on the process it is a part of

Lack of process transparency – inbuilt step by step monitoring providing more clarity.

Deployment limitations – allows greater process complexity in which AI can utilise for higher quality answers.

Tight regulations and certifications – processes clearly defined to stop AI from cutting corners

Externalities & novelty – clear processes and advanced monitoring allow application of theory of constraints even in extremely complex procedures.

At DRS the combination of these two emerging technologies excites us for the future of production planning and operations. When utilised correctly the potential gains revolutionise the way we work and what is possible in engineering.

As Engineers, can AI adoption alone solve our current challenges? We believe that AI alone fundamentally cannot address the requirements of production process and planning. We see AI as an accelerant, getting you to where you asked it to take you faster, but how do you know it understood the questio...

29/01/2026

As Engineers, can AI adoption alone solve our current challenges?

We believe that AI alone fundamentally cannot address the requirements of production process and planning. We see AI as an accelerant, getting you to where you asked it to take you faster, but how do you know it understood the question or that you even asked the right one?
How AI is deployed within a system is crucial to a successful outcome, without the correct limitations and scope, risk of failure is increased. Legacy systems were not built with AI in mind, therefore do not always have the required functionality to enable successful deployment.

So, what are the key considerations when deploying AI in production?

Reduced efficacy in closed systems – reduced data set = lower quality answers

Generalisation bias – will move towards average which in niche industries is counter productive

Lack of process transparency – unclear decision-making leads to limited insights and process development

Deployment limitations – limited by complexity of system it is within, simple system = simple answers

Tight regulations and certifications – AI is outcome focused not process focused, clashing with current engineering standards.

Externalities & novelty – factors outside its dataset are overlooked and hence their impact is not considered.

So how do we mitigate these limitations? At DRS we deploy AI within an orchestration framework working in symbiosis to unlock AI’s full potential. Which we will explore in more detail in our next post.

23/01/2026

Engineers are extremely familiar with process and mathematical models; so why is this not as effectively applied to our operations or planning processes?

Procedures are everywhere in engineering and process modelling is often produced alongside this to aid manufacturing and maintain high production quality. However, this never extends into the planning processes that accompany them.

Resulting in two separate worlds within every company, what the system thinks is occurring and what actually occurs on the factory floor.

In Job Shop and Batch production methods this is further exacerbated from the variety of procedures and products that are utilised in parallel and over time. Historically resulting in a single operational and planning process having to generalise its models to cover all eventualities loosely.

DRS believes that previous technological advancements in software have heavily favoured larger volumes and more continuous forms of manufacturing, however this is set to change.

Utilising emerging AI technology, Orchestration and adopting a new production process led operational and planning model approach. Production processes can now be placed at the centre of the software that determines the operational and planning processes of the company. Prioritising what makes any manufacture great.

Enabling the ability to have distinct operations based on the type of part being produced, if there are first article considerations, the customer it’s for and more.

14/01/2026

As a young and ambitious company who are pursuing real positive change in the market these awards from CEO Monthly for Most Influential CEO 2026 - Engineering Tech Innovation (United Kingdom) & Best Engineering Operations Software Provider 2026 has been genuinely the best validation we could wish for.

Our inclusion in this month's issue is something we are proud of and is a great introduction to who we are. You can see the full publication here: https://www.ceo-review.com/issues/january-2026/12/
A huge thank you to CEO Monthly for recognising Kyran Griffin our CEO and the DRS team. We are truly grateful to J36 our tech partners and our investors who have believed from the very beginning.

24/11/2025

How do we build trust in the process of changing ERP software?

Changing ERP has historically been a very challenging process. With the main technical challenges being data migration, integration to other existing processes and technical understanding of the existing system.

When incorrectly managed, this can lead to disruption for your business, incomplete or incorrect deployment and negative sentiment among employees. This has led to a large incumbency bias toward existing platforms, meaning companies often keep providers for longer than they are happy with the product/service provided.

Utilising AI in the transfer process drastically reduces this headache. Allowing for seamless migrations as it interprets the existing data structure and transfers to new system whilst also increasing its quality, through cleaning and refinement of poor data.

This could make a drastic shift in our markets make up as customers can more freely, switch adding a dynamism to the sector that has not before been seen.

What are your past experiences of switching ERP systems?

05/11/2025

What size companies have the most to gain from the introduction of AI?

The Entrepreneurs’ Organization believe that small business have the most to gain, stating “Artificial intelligence can transform the way small businesses compete, offering powerful tools that boost efficiency, customer service, and marketing. By leveraging AI, even small teams can operate with the precision, scale, and professionalism once reserved for large corporations.”

At DRS we believe that this potential upside is magnified due to the production methods deployed by SMEs in the engineering sector.

Large, centralised mass manufactures have gained from the adoption of bespoke monolinguistic planning systems of the previous era. As they could afford the cost of expensive bespoke systems and due to continuous manufacturing methods have singly defined production process, that can be mapped directly without need for inbuilt flexibly.

SMEs in engineering tend to focus on the high value/low volume market, relying on a batch production method to achieve diverse product demand. This left them stranded in the middle of an increasing bifurcated offering of expensive bespoke solutions and reduced scope generic products.

The introduction of AI allows for a new perspective on planning software for SMEs, allowing them to capitalise on the gains of centralised planning while retaining their ability to be flexible and reactive to customer demands.

Where do you think companies in engineering will see the largest boost from AI?

31/10/2025

What are the key challenges specific to the engineering sector?

Previously we discussed the general trend of dissatisfaction with ERP in the current market as referenced from Gartner. https://www.linkedin.com/feed/update/urn:li:activity:7386444025177722880 and the opportunities missed by existing vendors .

This time we are going to focus on what challenges are specifically affecting engineering.

We have identified 4 key areas:

1. Increasing operational complexity
2. Diverse production practices
3. Productivity gaps
4. Hardware Focus

Increasing operational complexity is a challenge for software in any sector however in engineering there is 3 distinct forces driving the development of requirements over time. Being development in business practice, engineer processes and software innovation. This constant multivariate influence requires software that responds to all 3 pull factors, which is difficult to achieve in a single solution.

Diverse production practices are a unique challenge. Production models that many ERPs system are based upon are not an accurate representation of the real-world implementation. Each production line is unique and software that has no mechanism to facilitate this will ultimately result in a generalisation of processes. The net impact of this being an accelerating deterioration in effectiveness and quality of product delivered to each individual customer.

Productivity gaps are common as production has many processes with legacy software e.g. CAD, CAM etc. This results in information getting “siloed” and workflow being disrupted as information is translated from one system to another. Decreasing process efficiency, lowering productivity and an inevitable loss in data quality. An Interconnected system with coherent feature design both internal and externally is required to combat this. A “Walled Garden” approach simply is ineffective in this context.

We define hardware focus as the tendency to seek out solutions to efficiency problems by the updating or introduction of new/more tooling and/or machines. Engineering companies tend to overlook software as a solution to their problems due to speciality bias effecting their decision making. Resulting in massive resources being allocated to new machines where a change in software would have provided a larger positive impact for less cost.

Are they anymore that effect you at your company?

Why is there a growing frustration with ERP for process optimisation? Gartner’s research led them to this conclusion “Unparalleled negativity greets enterprise resource planning (ERP) — with good reason: More than 70% of recently implemented ERP initiatives will fail to fully meet their origin...

24/10/2025

What do you think are the missed opportunities by current vendors?

Previously we discussed the general trend of dissatisfaction with ERP in the current market as referenced from Gartner. https://www.linkedin.com/feed/update/urn:li:activity:7386444025177722880/?actorCompanyId=108297458

In today’s post we will explore the missed opportunities in operations software. We have identified 4 main areas.

- Lack of specialisation
- Bifurcated market offering
- Limited Flexibility
- Barriers to Innovation

The engineering sector is mostly overlooked by larger vendors due to its complex and niche nature resulting in generic solutions being badly implemented to a very specific software specification. Creating room for smaller actors to make a large impact in this space, through the offering of a focused engineering software.

Software in this market has bifurcated into two very distinct offerings. The first being fully bespoke solutions that have long implementation windows at an enormous cost, or off the shelf products that are general in nature and narrower in scope. This leaves most companies stuck in the middle. Not having a high enough budget for a fully bespoke solution but have too specific procedures for an off the shelf option. Therefore, a composable and configurable solutions is needed to service SMEs in the market.

Rigid solutions have been a biproduct of system design philosophy and limitations of older technological constraints. This simplification of processes was required for system speed and scalability in the past however, this came at the expense of the user. Emergent technologies and AI allow the creation of flexible systems without the same drawbacks, prompting the rise of products that truly adjust to your individual needs.

Older systems are limited by platforms in which they were built on and there comes a time where these simply can no longer be updated and a full rebuild is required. This provides a massive benefit to new companies as they can build upon brand new architecture gaining all the benefits of the most recent technological innovations with no barriers.

What other opportunities do you think are present in this market?

Why is there a growing frustration with ERP for process optimisation? Gartner’s research led them to this conclusion “Unparalleled negativity greets enterprise resource planning (ERP) — with good reason: More than 70% of recently implemented ERP initiatives will fail to fully meet their origin...

21/10/2025

Why is there a growing frustration with ERP for process optimisation?

Gartner’s research led them to this conclusion “Unparalleled negativity greets enterprise resource planning (ERP) — with good reason: More than 70% of recently implemented ERP initiatives will fail to fully meet their original business use case goals.”

The failure of companies to meet their use case goals we believe can be broken down into these key areas

- Diversity of available solutions (unclear what solution is best for you!)
- Rigid solutions (restricting you into a generalised solution)
- Misalignment with your processes (forcing compromise on business practice)

High failure rates clearly have contributed to negative sentiment however this is still present among companies where implementation is considered a success. What may be causing this?

- Increasing requirements over time (processes outgrow solution reducing effectiveness)
- Reduced collaboration over time (slows required enhancements further separating actual workflows from implementation)
- Low user end adoption (disgruntled users reduce effectiveness as working outside of the product increases over time)

Part of Gartner stated solution is too “replace monolithic legacy ERP with flexible capabilities”.

At DRS this solution directly aligns with our approach to crafting software solutions for the current engineering market.

Over our next few posts, we want to dig deeper to the causes and potential solutions for this. Would be great to get your thoughts on:

- Growing frustration with current solutions
- Missed opportunities of current software solutions
- Key challenges specific to the engineering sector

17/10/2025

We are excited to announce our CEO, Kyran Griffin will be speaking at the third addition of Unplugged by MQube

His presentation will explore the critical introduction of AI in an engineering context, delve into its application structure for managing complex systems using the Theory of Constraints, and discuss its power in resolving externalities and novelty in system design. He will also provide specific insight into the relevance and application of these advancements within the UK engineering sector.

To join Kyran at this event and get involved in the discussion head to the Meet Up link below: https://www.meetup.com/mqube-technology/events/311532745/

30/09/2025

What do you think of the future of British Engineering?

At DRS we believe that the UK is perfectly positioned to capitalise on the next wave of industrial innovation. Commonly known as the fourth industrial revolution or industry 4.0.

The UK has always had a decentralised element to its engineering, which has cultural roots in the industrial revolution and the ground up nature of early industry. This runs in conflict to the trends seen in the late 20th and early 21st century, of increasing centralisation and scale of manufacturing.

This time saw the introduction of computers, central databases and fixed production planning in to manufacturing. Which allowed the accurate planning of singularly defined complex production. Incentivising centralisation, higher volume and lower diversity of products. It is in this framing that the narrative of the decline of British manufacturing is seen through. As the UK’s difficultly to compete with countries like Germany and increasingly China at higher volumes led to negative sentiment.

Where the UK thrives is instead in the high value production market, following a batch production method at lower quantities. This style of manufacturing has been underserved by the technological advances of previous years. As the flexibility and diversity required to produce these products, breaks the rigid and singularly defined production models that planning software relied on.

Therefore, this means that British engineering has a lot to gain from the growth in AI and machine learning, where systems can embrace flexibility, with advanced decision making embedded within their procedures and planning systems. Unlocking the same advantages in planning, efficiency and traceability that we have seen at higher volumes and bring them to the higher flexibility and lower volume market.

Leaving British engineering perfectly positioned to thrive from the adoption of AI and emergent technologies.

Let us know your thoughts?

.0

26/09/2025

Passionate about transforming engineering?

At DRS we are passionate engineers working to create software to elevate engineers’ performance to a new level, by removing as many operational barriers as possible.

As a business we want to serve engineering, which has historically been overlooked by the software industry due to its complexity and niche nature. We plan to change this!
We believe that digitisation has placed growing administrative and operational burden on production, suffocating creativity and versatility in the sector. We want to utilise emergent technology to streamline engineering processes and empower engineers to maximise their talents, contributing to them facilitating positive change to the world.

DRS wants to do what is best for industry and are not interested in just selling you product. We are interested in providing a service that continues post sale, to positively impact your processes as your company grows and develops.

“DRS will be a force for good”, says CEO Kyran Griffin, “Our, ambition is to revive British engineering by transforming its software, promoting growth and increasing positive market confidence.”

DRS will be the difference maker, allowing many engineering companies to grow exponentially. Measuring ourselves by the positive change brought to our customers, rather than the direct success of our company.