Frequently Asked Questions

We specialise in AI, machine learning, NLP, data science, and LLM and GenAI consulting. Our services range from structured entry points for businesses getting started with AI, including opportunity assessments, feasibility studies, and proofs of concept, through to full custom AI implementation. We also offer AI strategy and innovation consulting, applied research, and ongoing support.

Businesses of all sizes across most sectors, from early-stage startups to large multinationals. We have worked across healthcare, finance, legal, retail, manufacturing, and more. What matters more than size or sector is whether there is a genuine opportunity for AI to make a difference.

We are based in Dublin, Ireland, and work with clients globally. Most of our work can be delivered remotely. We are happy to travel for workshops, stakeholder sessions, or wherever on-site presence adds real value.

As an independent AI consultancy, we do not carry the overhead of large consulting firms. That means senior-level expertise on every engagement: work is never delegated to junior staff, and our rates reflect our actual costs rather than supporting large corporate structures. We are also focused exclusively on AI, which means a depth of specialisation that generalist firms typically cannot match.

The initial call is a genuine conversation, not a sales pitch. We will discuss your business, the challenges you are facing, what you are hoping AI can do, and what you have tried before. From that we can give you an honest view of whether and how we can help, and what a realistic scope and cost might look like. There is no obligation to proceed.

No. If you already have a clear use case and a defined problem, you can start with a feasibility study, a proof of concept, or go straight to implementation. The opportunity assessment is for businesses that have not yet identified where AI should be applied. We will always recommend the most appropriate starting point for your situation.

For projects where the outcome is less certain, we will often recommend a feasibility study first: a focused, rapid check that answers the core technical question before any substantial build begins. Where a build is proceeding, we work in an Agile way so progress can be reviewed at regular intervals, and the approach adjusted or paused if the results are not meeting expectations.

Yes. We treat the confidentiality of your project as a baseline requirement, not a special request. We are happy to sign an NDA before any substantive discussions.

No. We work with clients across the full spectrum, from technically sophisticated engineering teams to business owners with no AI background. Our job is to translate the complexity, keep you informed and in control, and ensure any solution is understood and operable by your team, not just by us.

Not necessarily. The right starting point depends on the use case. Some AI applications require substantial, well-organised historical data; others can begin with what you have and grow from there. We will assess your data readiness as part of any engagement and give you an honest view of what is needed before useful work can begin, including if it is not the right time to proceed.

Not necessarily. Most AI systems can be deployed on cloud infrastructure, and for the majority of businesses this is the right approach. There is a wide range of options across AWS, Google Cloud, Azure, and specialist AI platforms, and the right choice depends on factors including your existing systems, security and compliance requirements, budget, and how much operational control you need. Part of our work is helping you make that decision sensibly rather than defaulting to the most expensive or most complex option. Where you already have infrastructure in place, we design solutions that integrate with it.

They are overlapping fields rather than mutually exclusive categories. AI and ML cover systems that learn from data to make decisions or predictions. Data Science uses statistical methods to analyse data and surface insights, often using ML techniques. NLP (Natural Language Processing) is the branch of AI that deals with understanding and generating human language. GenAI and LLMs are a more recent development: models capable of generating text, code, and other content that overlap with both ML and NLP. In practice, a real-world solution will often draw on more than one of these areas.

Pricing is tailored to each engagement based on scope, complexity, and the services involved. For most projects we work on a fixed fee, which gives you cost certainty from the outset. For ongoing support or clients with varying needs, we also offer day rates and retainers. As an independent consultancy, we do not carry the overhead of large consulting firms, which means senior-level expertise at competitive rates, without the inflated fees that come with supporting large corporate structures. The best way to get a realistic indication of cost for your situation is to start with a free introductory call.

Yes. Every implementation includes documentation, team training, and a post-deployment support period so your team can operate the system independently. Beyond that, we offer ongoing support through retainer arrangements if you need continued development, enhancements, or simply someone on hand as your needs evolve.

Deliberately and early. We do not want clients to be dependent on us for things they should own themselves. We document as we build, involve your team throughout the process, and structure the handover so that running and iterating on the solution is within your team's capability, not just ours.