Understand
We review how the business works with the people running it, using real customer journeys, tasks, systems and data.
Find the right AI opportunities for your business
DabApps helps SMEs decide where AI could improve their products and day-to-day work. We review your processes, systems and data, test the most promising ideas and create a practical plan for implementation.
Where is work getting held up?
Staff may be copying information between systems, preparing the same documents repeatedly or searching through past work to answer a customer. You may already have an AI prototype, but no agreement on who will use it or how it will fit into everyday work.
Our AI strategy and transformation engagement looks across these problems to help you choose where to invest. The aim is to identify changes that could save effort, improve a service or help your team support more customers, with evidence to guide the next decision.
If you need advice on a specific product idea, technical decision or risk, our AI consultancy offers focused guidance.
AI DISCOVERY
What we review
We look at the work in context, including what customers value and what staff need to get it done. Conversations with business leaders, the people doing the work and those responsible for systems and data help us understand both the opportunity and the constraints.
- Customer journeys and the work behind them
- Repeated tasks, handovers and workflow exceptions
- Existing software and how systems share information
- Data quality, access and permissions
- Where human judgement and approval are needed
COMMON STARTING POINTS
When an AI transformation review helps
This engagement suits SMEs that need a shared set of priorities and a plan for adoption. It gives your team a way to compare competing ideas, question an initial solution and decide what deserves further work.
- Too many AI ideas, with no agreed priorities
- Prototypes without a delivery plan
- Staff repeating work across disconnected tools
- Uncertainty about whether to buy software or build it
- A personal service that needs to support more customers
How we assess your AI opportunities
Prioritise
Together, we compare opportunities against business goals, feasibility and risk, and agree which ideas are worth testing.
Test
Where an assumption needs evidence, we use prototypes or proofs of concept to explore it with your team before committing to a build.
Plan
We bring the findings into a practical roadmap, showing what to tackle first, what it depends on and what needs further investigation.
DECISIONS AND DELIVERABLES
What you receive
You receive findings and recommendations that help your team decide what to do next. We agree the deliverables around the scope: these might include a customer journey map, a tested prototype or a technical outline for the first phase. DabApps brings product design and software engineering into discovery, so the plan considers the systems, permissions and ongoing support needed for implementation.
- Prioritised opportunities with reasons to pursue or set aside each one
- A map of the workflows and systems that need to change
- Prototype findings and assumptions still to test, where needed
- Recommendations for existing tools or custom development
- A phased implementation roadmap with dependencies and next decisions
AI opportunities explored with our clients
For Take Me to the Moon, reviewing the whole customer journey changed the initial AI idea and produced a prototype and phased development scope. The projects below show how discovery and technical testing inform where to invest in AI.
Take Me to the Moon
We helped a specialist travel team imagine a more personal digital journey: a mobile companion prototype combining itineraries with access to human support.
Emvelo
We built an operator decision-support system for Emvelo, combining plant forecasts and optimisation recommendations in an operator interface.
Brace for Impact
ImpactIO says our platform analyses sustainability documents in minutes, speeding up reporting and creating a new service to sell.
What happens after discovery
The roadmap sets out a first useful step and the decisions needed before implementation. That could mean adopting an existing product, improving how data moves between systems or commissioning a new capability. We consider what staff will need to change, how results will be checked and who will own the work.
Where custom software is justified, our AI product engineering service can build and integrate it. If a specific question needs more investigation before you proceed, AI consultancy can help assess that decision.
Questions about AI strategy and discovery
Who should take part in AI discovery?
Include someone who can agree business priorities, the people doing the work and whoever understands your systems and data. We bring product, design and engineering perspectives, and agree who needs to join each discussion around the opportunities being explored.
Do we need an AI idea before we start?
No. Bring the work you want to improve: a slow handover, repeated administration or a customer experience that is difficult to deliver as demand grows. Existing ideas and prototypes are useful inputs too. We assess them alongside the wider workflow.
What if an existing product already solves the problem?
We recommend using an existing product when it fits the need. The review considers how it would work with your data, systems and staff, including any integration or process changes. Custom development is one possible outcome, and we may also recommend improving a process without AI.
Will a prototype be ready for everyday use?
A discovery prototype tests an idea or assumption. Before it becomes something staff or customers rely on, it needs an agreed delivery scope covering implementation, permissions, evaluation, integration and support. We make that distinction clear in the roadmap.
How are the scope and cost agreed?
We start by discussing the areas of the business to review, the people involved, access to systems and data, and the questions that may need prototyping. These shape the proposed scope, deliverables, timing and cost. Implementation is scoped once the next steps are clear.
Planning for AI adoption
Ed Hickey explains how to assess an implementation partner, and Jamie Matthews sets out the context, permissions and human control that AI systems need.
Discuss your AI opportunities
Tell us where work is getting held up, what you've already tried and what you'd like to improve. We'll discuss whether an AI discovery engagement would help.