Getting the most from AI as part of your bespoke software
Executive summary
AI is positioned as one of the most powerful levers for business efficiency, there is no question that it can have huge impacts on digitising manual task and spreading up processes, but only when it is implemented and used correctly.
As we all journey into the new world of business, technology and work, every sector, from business services, to manufacturing, built assets and facilities, is considering the impact that AI could deliver. As experts in bespoke software engineering and technology we share our view in this guide. We believe that at this juncture AI needs to be delivered as one part of a bigger modernisation and software engineering project, and any AI projects, must be scoped in line with software updates that lead to modern and flexible systems that are designed around your organisation and its customers' needs. Attempting to bolt AI onto outdated systems that have not been managed or kept up to date will only result in failure; as the data foundations for AI would simply not be there and it is this quick fix approach that can be a common reason projects fail. A tailored approach to systems improvement using bespoke software development, combined with modernisation, unlocks AI’s true potential.
“The future of bespoke software lies in its ability to solve real-world problems… bespoke software and AI together can deliver efficient and practical business outcomes at scale.”
David Ritchie, Propel Tech.
Guide Content:
- Starting your AI modernisation journey
- Developing your value-driven AI use case
- Integrating AI models & APIs into bespoke platforms
- Managing change in AI-powered software modernisation projects
- Future-proofing: bespoke AI in a continuous modernisation journey
- Takeaway
Starting your AI modernisation journey
Modernisation clears the ground for AI, but bespoke development and custom software engineering is the construction. Without expert developers, systems that work, clean usable correctly scoped data, custom-built integrations, interfaces, and data flows, AI models cannot deliver consistent, reliable or safe results - regardless of how modern a system is.
Propel Tech specialises in bespoke systems development and in building bespoke integrations that are robust, well planned and effective, at the start of any project is a review of the “As is” and critically a data review is a large part of this. We look to understand the data schematic, how complete the data is, what it is needed for and where it is stored? In any AI focused project this starting point of assessment and data review is critical as without it, it is impossible to translate AI capabilities into tangible business improvements.
Lets face it, legacy systems often monolithic, tightly coupled, and brittle, as such, on the face of it, this makes them poor hosts for AI. They lack modern APIs, structured data pipelines, and flexibility. Adding AI on top of such systems typically results in fragile integrations, inconsistent model inputs, and high costs. This is where custom software development is critical - acting as the join that allows legacy systems to take advantage of new AI efficiencies.
When legacy systems are in play we find that there are huge data inconsistencies that need managing before a system can be improved, this is even more pertinent when you consider adding AI into any systems modernisation.
Bespoke software development can act as the enabler of modernisation of legacy systems, you don't need to throw away your existing systems but you do need to audit what you have and look at how your systems are working, its data completeness and how fit it is for purpose.
The start of any modernisation project that encompasses the desire to add in AI functionality is to look at your data foundations and work to re-architecting outdated platforms.
Propel Tech’s legacy software modernisation services combine deep technical knowledge with bespoke development to deliver exactly this environment.
Modernisation-first checklist
- Inventory of core systems & data completeness dependencies and flows.
- Bespoke API requirements designed for integration and scale.
- Event-driven or streaming data pipelines.
- Security-first architecture (IAM, encryption, audit trails).
- CI/CD pipelines to enable continuous delivery.
Developing your value-driven AI use case
Many organisations are adopting AI opportunistically, experimenting without measurable goals, and starting on an implementation without checking the data foundations, custom solutions or legacy systems are solid, this test and learn approach is great - but it needs to be conducted with caution as it can be costly, embed the wrong view of AI, and fail to deliver returns. In short, these efforts rarely scale.
Once you have audited the AI opportunities in your business, fully understanding the goals and issues that your organisation would like AI to solve, bespoke software can then provide the bridge between modernised systems and targeted AI applications.
With tailored solutions, AI agents, and llm’s can be directed at high-value use cases, we are already seeing these use cases across different sectors such as:
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Predictive maintenance
in manufacturing, built into custom dashboards.
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Process optimisation
in logistics, driven by bespoke workflow automation.
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Forecasting
in retail and finance, powered by modernised data pipelines.
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Customer support augmentation
with AI-driven assistants, tightly integrated into bespoke CRM platforms.
Don't know where to start? To get you on the right track we would suggest developing a prioritisation scorecard:
Data quality · Impact · Complexity · Regulatory risk
If you need more help in planning and scoping please get in touch with our team who can offer extensive support with AI consultancy.
“AI delivers its real value when embedded in bespoke software solutions designed around your business processes, this is where we see efficiency and return on AI.”
Chris Kirkham - Propel Tech
Integrating AI models & APIs into bespoke platforms
As we have established AI models are only as good as the data and the use case on which they rely. When integrating AI models robust and resilient practices should be implemented to safeguard AI solutions in terms of both data quality and security. Unlike traditional systems, AI models ingest and act on data in real time, often collected via an automated assistant which heightens the risk of inaccurate inputs leading to flawed decisions. This increases risk, potentially resulting in things going wrong quicker and having a greater impact.
In manufacturing for example, poor data quality such as unverified production times, outdated orders records or missing labels, stock or liabilities can lead to inaccurate risk classification. Whilst these risks are not new, if AI is processing multiple orders on a manufacturing line and making errors, the size and scale of an issue could quickly become significant. Moreover, AI enhanced systems can make and propagate decisions autonomously, increasing the requirement for robust data governance. And strong data foundations.
Bespoke development when done correctly can ensure modernised platforms are designed with AI integration in mind. Propel Tech delivers AI-powered business software by:
- Designing API gateways to expose AI services cleanly.
- Embedding RAG (retrieval-augmented generation) into custom applications.
- Building MLOps pipelines within bespoke architectures for governance and scalability.
- Developing hybrid approaches — combining third-party APIs with bespoke models to suit business needs.
Managing change in AI-powered software modernisation projects
“Treat AI as a capability you are building - not a one-time project. Pair it with bespoke software and clear ownership.”
Gartner 2025
Even the most robust technical work falters if employees resist change or stakeholders lack confidence. AI is scary, there is a fear for many that it will erode their jobs and their usefulness in work, which is not unexpected given the actual realities that jobs are changing and AI is being looked to to support business cost savings and efficiencies.
“Humans are territorial in nature, meaning we like to feel in control in order to feel safe. If something is unknown to us, and therefore outside of our control, like AI, then we are always fearful of it. The psychology behind this is rooted in the human need for control and understanding.”
Hannah Starkey - HR Manager Propel Tech
To manage this fear, and in some cases well founded concern, it is essential to where possible keep teams involved and engaged along the process and put humans at the centre of technology changes is a proven method to getting more out of your technology modernisation be this with or without AI as a component.
Bespoke software development has always been about solving human problems and as such it allows any AI implementation of changes to be managed transparently as part of a structured technology adoption process: interfaces are designed around people, reporting is embedded, and AI outputs are tailored to support rather than replace. Propel Tech when working on client projects ensures smooth adoption through custom software solutions and structured change programmes.
AI modernisation team change checklist
- Executive sponsorship - get buy in from the top will make it easier to get everyone of board.
- Clear role definitions (human vs AI). Ensure everyone is on board with how AI will support, change or enhance their roles.
- Bespoke training embedded in the software rollout. DOnt skimp on training - without it the AO tool could be more costly than useful.
- KPIs tied to AI adoption. Set some clear division, business and individual KPI’s that link to the AI adoption - this way you can track its effectiveness and use.
Future-proofing: bespoke AI in a continuous modernisation journey
AI models degrade over time, and static systems make retraining impossible.
Bespoke development ensures that systems remain adaptable. Propel Tech designs modernised platforms with continuous retraining, monitoring, and upgrade cycles baked in. With AI-driven process optimisation UK, businesses can keep AI valuable and aligned with changing business needs.
Ongoing AI Model lifecycle review checklist
- Implement dataset versioning.
- Put in place bespoke retraining pipelines.
- Allow for and plan continuous monitoring for drift.
- Schedule regular infrastructure updates.
Governance & ethical considerations
Bespoke software allows AI to be deployed responsibly. Propel Tech embeds governance into the architecture: model registries, audit logs, and human-in-the-loop checks. Compliance with GDPR and UK government AI risk guidelines is designed in from day one.
Takeaway
AI is not a quick fix bolt on bolt-on. It is a capability that can thrive but only when embedded correctly as part of custom software engineering, on strong data foundations and as part of a bespoke, modern software schema. For UK SMEs and enterprises, the right path is clear: modernise legacy systems with bespoke development, build the right data foundations, take the team on the journey, and design tailored AI use cases, then build governance into the software, processes and data themselves.
Want to explore how Propel Tech can modernise your systems and deliver AI-enabled bespoke software? Talk to our experts.
Your partners in possibilities
As experts across existing and new technologies, we don’t simply solve software problems, we find solutions that help manage change so that your business thrives and grows.
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