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Discover concrete examples of R&D tax credit qualifying projects across IT, manufacturing, and pharmaceuticals. Learn to identify eligible activities in your business.
Innovative companies in the UK can access a vital government support, R&D tax credits. The incentive rewards companies investing in R&D with tax relief. But how do you know if your projects qualify for this generous tax credit?
R&D can happen in workshops, on factory floors, in software development teams, and in countless other settings across industry. However, the definition of R&D doesn’t help you visualise the kinds of activities you should be looking for.
In this article, we’ve anonymised and summarised some of the projects our clients have actually claimed R&D tax relief for to give you an idea of projects that could qualify.
Before diving into specific examples, let’s get to understand the qualifying criteria. HMRC has clear guidelines, and a project must tick all these boxes:
It's equally important to understand the red flags:
The key distinction is between commercial innovation (doing something new for your business or market) and technological advancement (improving what's possible in the wider field).
The IT sector accounts for over 25% of all R&D tax credit claims, making it one of the most common areas for relief. However, there's a widespread misconception that all innovative software development qualifies. Using cutting-edge frameworks, implementing AI, or building a novel app doesn't automatically make something R&D. The critical difference is between implementing existing technologies and genuinely advancing what's technically possible.
A data analytics company needed to process millions of handwritten data entries from various sources. The volume was unprecedented, and the handwriting varied significantly in quality and style. Existing intelligent character recognition (ICR) tools simply couldn't handle the complexity at this scale; they either produced too many errors or required excessive manual intervention to validate and correct the results.
The company needed to reduce operator involvement by at least 90% whilst maintaining accuracy across this diverse dataset. Standard ICR solutions would flag uncertain characters for manual review, but at this volume, manual validation would make the entire system commercially unviable.
The Technological Uncertainty
The core uncertainty was whether automated data validation could work reliably across such diverse and unprecedented data scenarios. Could a system be developed to authenticate entries across specific complex fields without constant manual intervention? And critically, when the system did encounter problems, could it fail gracefully without jamming or damaging the broader workflow?
Existing best-practice methods had been tested and found insufficient. No commercially available solution could perform automatic business logic routing for these previously unseen data scenarios.
The R&D Activities
The development team embarked on systematic experimentation to overcome these challenges. They designed a novel automated data validation architecture specifically to capture and authenticate entries in the most problematic data fields.
Through testing, they discovered that the system's recognition algorithms sometimes incorrectly identified data, triggering editing protocols. This required developing an entirely new redundancy mechanism: a backup system that could handle scenarios where the primary automated validation failed for specific field types.
The work also involved creating new methods to reduce computational overhead dramatically. The team needed to engineer approaches that hadn't been documented in existing literature, testing different algorithmic strategies to achieve the required 90% reduction in operator input.
Why This Qualified
This project qualified because it advanced beyond existing ICR capabilities in a measurable way. It addressed genuine technological uncertainty that competent professionals couldn't readily solve with existing methods. The systematic approach of testing, encountering failures, and developing new solutions demonstrated the kind of experimental development that HMRC recognises as R&D.
This company develops software products and technology-enabled services in medical diagnostics. It had struggled with its proprietary algorithm library needing significant redevelopment for each new client and project it undertook. They wanted a flexible approach for building bespoke analysis pipelines that encompass data ingestion, preparation, analysis, and the generation of tailored reports for new use cases.
Within this project, the company later sought to expand the technology to include new data types, which would affect data ingestion, transformation, and rendering layers. The proprietary platform needed in-house development to achieve this.
The Technological Uncertainty
Changes to the structure, content and metadata of the data types affected each stage of the platform, especially at the visualisation stage. The team was unsure if and how the technology could be expanded upon to handle all new data types.
The R&D Activities
The expansion of the platform’s visualisation component to accommodate all data types required adapting both the data pipeline and the rendering logic. The team needed to develop a method to handle variable output structures and more complex interaction patterns, enabling end users to visualise subject timelines, cross-check data against expected outcomes, and explore how new datasets influenced outcomes.
By ensuring the platform could interpret any data produced, the system’s analytical and visual layers became fully interoperable, eliminating a previous constraint on the scope of decision support. However, further redesign was required to make the visualisation layer dynamically responsive to different data schemas without manual reconfiguration.
Why This Qualified
This project qualified because it expanded on the technological capabilities of data visualisation and analysis. The team overcame uncertainties in data manipulation to achieve an improvement to the platform and to data analysis methodologies in the wider field. Through systematic trial and error, the company exemplifies the R&D process that HMRC is looking for.
Manufacturing and engineering claims are nearly as common as those from IT, driven largely by the Fourth Industrial Revolution's emphasis on data, connectivity, and advanced automation. Often, R&D in manufacturing hides within "continuous improvement" initiatives, so companies may not realise they're doing qualifying work.
A manufacturer of plastic injection mould tooling faced a persistent problem with their ejection system. The traditional method used a fixed bar pushed by a hydraulic ram to eject formed components from the mould cavity. Whilst this approach had been effective for years, it carried significant risks.
When ejector plates became jammed or distorted, the powerful hydraulic ram would continue applying force, potentially causing serious damage to expensive tooling. The system had no mechanism to detect snags and halt operation before damage occurred. The company needed a safer, more reliable ejection method.
The Scientific Uncertainty
The fundamental uncertainty was whether industrial springs could replicate the force of a hydraulic ram whilst providing the "intelligent" behaviour of stopping when encountering resistance. This meant putting a validated principle (spring force) into an entirely new context, and it was unknown whether the approach would be technologically feasible.
Specifically, could springs generate sufficient pressure to eject parts from the cavity once they'd solidified and bonded? And would a spring-based system genuinely reduce the risk of jamming and tool damage?
The R&D Activities
The team began by developing a rear ejection method, positioning industrial springs between the ejector plate and the rear of the tool. However, this approach lacked a mechanism to prevent the ejector plate from remaining in position following ejection, requiring the development of additional securing features.
Initial trials revealed another problem: excess material from the moulding process would become lodged, preventing the ejection system from fully closing. This led to defects in subsequently moulded components.
The team then devised a completely different methodology, pulling the ejector plate from the front face of the tool instead. This worked better for shorter ejection lengths but had limitations for larger parts.
The next challenge was generating sufficient pressure. A series of tests determined the optimal number and configuration of high-tension springs needed. Transitioning from hydraulic to spring ejection also required modifications to the clearances and the introduction of specialised bushing materials to function as bearings, allowing smooth movement and reducing snagging. This was an innovation that emerged from the spring trials themselves.
Why This Qualified
This project applied an established principle (spring tension) in a completely new context (ejection system), creating genuine system uncertainty. The iterative experimentation—trying rear ejection, encountering failures, switching to front ejection, optimising spring configurations—demonstrated systematic attempts to resolve technological uncertainty. The appreciable improvement in ejection technology represented a genuine advance in the field.
A foundry needed to produce thin-wall castings that met a specific weight threshold whilst maintaining structural integrity. The standard aluminium alloy they typically used offered excellent mechanical properties after heat treatment but wasn't ideal for thin-wall applications.
The alloy had lower fluidity than alternatives, creating a thicker, sludgy consistency when molten. Operators would often raise the metal temperature to improve flow, but this had drawbacks: excessive heat could burn off essential chemical elements, altering the material's properties. Traditional approaches, such as adding specific elements or adjusting temperatures, failed to meet the objectives due to porosity, shrinkage, and other defects.
The Scientific Uncertainty
The core scientific question was whether the alloy's composition could be altered to enhance fluidity for thin-wall casting without compromising mechanical strength or other essential properties. This hadn't been validated in existing literature or industry practice.
Specific unknowns included: Could silicon content be significantly increased without adversely affecting heat treatment results? Would dramatically reducing iron content improve results without making the alloy impossible to produce reliably? And could proper grain structure be achieved with these new compositions?
The R&D Activities
The company embarked on an extensive programme of compositional experimentation. They reduced iron content well below standard specifications, which was a significant change requiring premium source materials instead of conventional recycled inputs.
However, this minimal weight reduction led to new challenges, with castings not forming completely. This triggered trials with significantly altered silicon levels, nearly doubling the content. This improvement initially looked promising but had adverse impacts on heat treatment results, as the treated parts didn't meet strength specifications due to the increased silicon content, which softened the alloy.
The team then experimented with adding sodium to the material, an uncommon approach for this particular alloy type. This attempt proved unsuccessful due to numerous casting defects, like sinks, porosity, and incomplete formation.
The work extended to investigating alternative alloy formulations entirely, adding different combinations of elements and employing sand-casting techniques to address grain structure issues. Each iteration revealed new challenges, requiring further experimentation to find viable solutions.
Why This Qualified
This project sought fundamental improvements to material properties through genuine scientific experimentation in metallurgy. The uncertainties were real, as standard approaches had failed, and the team needed to venture into uncharted territory with alloy compositions. The extensive iterative experimentation, with each attempt revealing new challenges requiring fresh solutions, exemplified qualifying R&D work.
Drug development obviously qualifies for R&D tax relief, but pharmaceutical R&D extends far beyond traditional clinical trials. Medical device development, new diagnostic methods, improved formulations, and novel treatment delivery systems can all qualify.
A medical device company was working on radiation therapy systems. Radiation beams used in therapy are invisible to the human eye and standard cameras, yet when these beams hit a patient's body, they create a detectable effect of a faint blue glow. This phenomenon has been known since 1937, but it had never been successfully detected on the human body during radiation therapy in clinical settings.
The challenge was compounded by the treatment room environment. Room lighting cycled on and off 50-60 times per second (standard electrical frequency). The detection system would need to capture fleeting moments of patient luminescence within the brief intervals of darkness between light cycles.
The Scientific Uncertainty
Several uncertainties existed. Would the effects observed in controlled, artificial environments match what occurred in actual clinical sites with real patients? Could a system be developed to capture patient luminescence within the rapid light cycling? And critically, could the device manage the high current and high voltage requirements whilst functioning reliably in an environment with elevated radiation levels?
Electromagnetic compatibility in such conditions was a critical unknown, as electronics behave unpredictably in high-radiation environments.
The R&D Activities
The development team had to create a high-frequency camera system capable of precise synchronisation with the treatment room lighting. This required designing an external tool to control lighting, ensuring exact timing with the camera systems.
The backend work involved assembling a custom printed circuit board (PCB) design. The device had to function in an environment with increased radiation, where electromagnetic compatibility presented unique challenges. The team needed to design custom firmware capable of operating under these conditions.
Existing relay switches proved insufficiently fast for the requirements, necessitating iterative experimentation with microcontrollers, capacitors, resistors, and relay features to create a lighting control system capable of microsecond-level precision. This level of timing control was essential to trigger exactly when the therapy beam initiated, thereby capturing the faint additional glow of the radiation.
Why This Qualified
The project developed an entirely new technological capability in radiation therapy. It addressed genuine electromagnetic compatibility challenges that required novel engineering solutions. The systematic approach to creating custom hardware capable of microsecond-precision timing in a high-radiation environment demonstrated clear R&D activity.
A medical technology company was developing devices for early diagnosis and non-invasive treatment of a common eye condition. Initial proof-of-concept clinical trials confirmed the technology was safe for human use but it didn't actually treat the condition as intended.
The approach was based on recent scientific discoveries involving light-based treatment, but translating this from theory to practical medical application presented numerous unknowns. No existing technology in the public domain could achieve non-invasive treatment for this particular condition.
The Scientific Uncertainty
Multiple scientific uncertainties existed. Could a device be created that would deliver sufficient energy safely to achieve the therapeutic effect in human patients? The mechanism of action wasn't fully understood. Was it possible to determine this mechanism well enough to inform prototype design?
Even if the device worked in laboratory testing, would it succeed in regulated clinical trial settings with real patients? Only clinical validation could determine success, but the team first needed to overcome the fundamental uncertainties about device design and energy delivery.
The R&D Activities
The team conducted extensive optical research and laboratory testing to determine optimal light wavelength and power intensity parameters. This required designing a completely new prototype optical system, including the targeting and alignment components.
The prototype redesign included increasing LED output power by re-engineering the optical path. External third-party testing validated the power output changes. The team then designed and integrated a custom targeting camera system with medical-grade interface hardware.
Testing revealed that the diagnostic optical system needed refinement to ensure light signals returned from the patient's eye without causing damage whilst still producing signals strong enough for analysis. This required multiple testing iterations.
Parallel to device development, the team conducted experiments to explore potential diagnostic parameters and investigate the mechanism of action. They performed spectroscopic analysis on laboratory samples, developing custom testing rigs to observe changes at the cellular level.
Clinical trials revealed additional device deficiencies, particularly around patient alignment. Following research to improve the existing alignment system, the team determined that the entire system was insufficient and required complete redesign, which was a significant setback requiring fresh innovative approaches.
Why This Qualified
This project sought to advance biophotonic medical technology in a field where no existing solution existed. The genuine scientific uncertainties about mechanism of action, optimal parameters, and device design required extensive testing and iteration. The work extended beyond engineering to fundamental scientific investigation, with clinical validation as the ultimate test of success.
Now that you've seen these examples, how can you spot qualifying R&D in your own operations? Start by asking your technical teams these questions:
R&D happens across industries and in settings you might not expect. The key thread running through all qualifying R&D is genuine scientific or technological uncertainty combined with systematic experimentation to resolve that uncertainty. If your business is tackling complex technical challenges that can't be solved through standard methods, you're likely undertaking qualifying R&D work.
Many businesses leave substantial tax relief unclaimed simply because they don't recognise their innovative work as R&D. Look at your projects with fresh eyes. That "tricky development problem" or "challenging engineering issue" might well represent qualifying R&D activity worth thousands of pounds in tax relief.
If you're unsure whether your work qualifies, or you'd like support in preparing a claim, Myriad's team of R&D tax specialists can help. With our zero-risk guarantee and over two decades of experience, we make the claim process straightforward.
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