Most workflow automation fails in the same place: it works in the demo and breaks on the first real exception. Businesses are full of exceptions, which is why the automation that lasts is built from a clear picture of the process rather than from a diagram of the happy path.
We build AI workflow automation for companies that have already outgrown the spreadsheet holding it together, and we start by finding out which parts are worth automating at all.
Not a chatbot bolted onto a website. We mean the work itself: a tender response drafted from your own prior submissions, supplier invoices read and reconciled without somebody retyping them, a quote that stops waiting three days for an internal reply, a month-end close that does not need a fortnight of manual assembly.
Some of that is classic rules-based automation and does not need AI at all. Some of it needs a language model because the input is messy human text. The useful distinction is not whether something is AI, it is whether the step is high-volume, low-judgement and reliably shaped.
It pays where the same shape of work happens many times a week, where the input is text or documents, and where a person can check the output quickly. Drafting, summarising, extraction, classification, retrieval and first-pass reconciliation all qualify.
It does not pay where the judgement is the job, where volume is low, or where being wrong is expensive and hard to notice. A model will produce a confident answer in all three cases, which is precisely the danger. We say no to these in writing, as part of the readout.
Agents that read across a business and act inside it are real and useful, and they are also where most of the current hype sits. The version that works has narrow scope, explicit permissions, visible reasoning and a person approving anything that leaves the company.
That is the rule our own products are built on: agents draft, people send. If a vendor is offering you autonomous action over customer-facing work with no human in the loop, ask what happens the first time it is confidently wrong.
It starts with an Operational Audit, so the build is scoped from a real process map rather than a wish list. Then FDE, forward deployed engineering, does the work: Nomad engineers in your building, on the tools you already own, with a working demo every Friday, because a nine-month build that reveals its problems at the end is how automation projects die. You own the source and the IP, and there are thirty days of support after handover.
Where it makes sense, builds run on Iris, a custom operating system for your business on a retrieval data core, so your data is somewhere a model can actually read from instead of scattered across systems that do not talk. Orchid, our flagship, goes further: it resolves what your systems and your people know into one permission-aware model and runs agents over it that find what is outstanding and draft the action. Both are described on their own pages, including what is not built yet.
Nobody wants to replace a working ERP to get automation, and you usually should not. Most of what we build reads from and writes to what is already in place: the accounts package, the CRM, the project tool, the shared drive. It does not ask a business to migrate first.
Where the existing data is the problem, that is a finding worth having early, and the audit surfaces it before anybody has committed to a build.
Irish businesses have a strong set of state supports for exactly this kind of work, from digital adoption grants to R&D tax relief. We flag the schemes that fit your situation in the discovery call; eligibility and terms are set by the agencies, so you confirm the details with your Local Enterprise Office, Enterprise Ireland or your accountant.
Up to €5,000
Local Enterprise Office
Covers 50% of eligible costs on software, training and IT configuration for businesses with 1 to 50 employees. It starts with a free Digital for Business consultancy through your LEO, and the work we do together maps directly onto what the voucher funds.
35% of qualifying spend
Revenue · R&D Tax Credit
From January 2026 the R&D tax credit is worth 35% of qualifying research and development expenditure, with up to €87,500 payable in the first year. Building genuinely new AI capability into your product or process may qualify; your accountant confirms eligibility.
€50,000 to €100,000
Enterprise Ireland
Investment for early-stage companies, ideally with a working MVP and early customer validation. Our MVP builds are designed to get you exactly there: something real in front of users that you can bring to Enterprise Ireland and investors.
100% discounted
CeADAR · EDIH for AI
Ireland's National Technology Centre for AI runs the European Digital Innovation Hub for AI, offering prototype development, training and support to start-ups, SMEs, mid-caps and public sector bodies at no cost. A Digital Maturity Assessment comes first. Subject to de minimis state aid limits.
Subsidised
Skillnet Ireland
Nomad is an approved Skillnet training provider, and Skillnet networks subsidise training for member companies. It is the cheapest route to getting a team trained properly, and the one most businesses do not know they already qualify for.
€5,000
Enterprise Ireland
Fund exploratory R&D with registered knowledge providers such as universities and institutes of technology. A useful way to validate a technical approach with academic expertise before committing to a full build.
Scheme details as published by the agencies, last reviewed September 2026. Amounts and eligibility change, treat this as a starting point for a conversation with them, not as financial advice.
A 30-minute call about your business, your tools, and where AI could realistically help. No deck, no pitch.
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