You already know AI is changing the economics of running an agency. Buying tools is phase zero. We build the systems that come next, then run and govern them.
Take the AI readiness assessment10 minutes. Email and agency name only. A report back within days.
Your team has ChatGPT licences and no playbook. Some people lean on it heavily, others not at all. No policy, no owner, no shared toolset, because client work always wins.
Meanwhile the team ships what HBR named workslop in 2025: AI output that looks polished but creates rework, dilutes your voice and quietly erodes client trust. Most MDs never see it.
Your clients are reading the same headlines you are. They will ask where the AI savings are, and how you're using it on the work you do for them. The agencies with an answer keep the margin.
One thing we should say plainly: the value of your agency is human. The brief, the judgement and the client relationship stay with your people. We build the systems that compress everything in between.
Every engagement starts with a written report on your agency: your score across five dimensions, where you sit against comparable independents, and the three margin opportunities you're not yet capturing. The free assessment version arrives within days. The £499 audit goes deeper.
Sample report shown with illustrative data. Yours is built from your assessment answers, benchmarked against agencies of your size and discipline.
We benchmark you against comparable independents and name the margin you're leaving on the table. You leave with a roadmap you can start on Monday.
We build the highest-impact agent from your roadmap, the one the audit ranks first. Scope and price reflect its complexity: integrations, data sources, automation depth. Your team uses it day to day.
Implementation, governance and a monthly hour with you so the team sees the MD experimenting. This is where the margin compounds.
I'm Dan O'Sullivan and I run Daio. For more than 15 years my work has been one thing: take frontier technology and make it speak the operator's language.
I started as a secondary science teacher through Teach First. By 2013 I was building AI-powered learning before generative models existed, and co-authored a peer-reviewed best paper on conversational AI tutors.
Then a decade in commercial roles. I was first employee and COO of a coding-education startup Roblox later acquired. After that, commercial lead at a kid-safe platform, where I brought Paramount, Universal and Cartoon Network on board, technology that put child safety first and gave families a real alternative to Big Tech.
Today I'm Commercial Director at an a16z-backed game studio, where the job is agencies: selling into them, co-pitching alongside them to their clients and working inside their teams. I run AI agents across my own operations too, built and maintained by me.
So AI for agencies is the same job from a new angle. I already work with agencies every week and run these systems myself. Daio is small on purpose: I scope and build the work, so you deal with the person solving your problem, and I take on few clients at a time.
That is the common experience and it is a fair place to start. Most AI projects return nothing: MIT Sloan put the failure rate at 95% in 2025. In agencies the reason is usually the same one. The licences got bought, nobody owned the change, and the work of fitting the tools to how you actually deliver never made it onto anyone’s calendar, because the client work always came first. So the thing that changes the outcome is not the technology itself. It is whether someone owns that fitting work and keeps it running once the novelty has worn off. That is the job we do, and if the audit finds nothing worth building we will say so.
Nothing without your sign-off. We build inside your accounts and your stack wherever possible, so your data stays under your control and your agreements. Where a build touches client material, that's scoped explicitly, covered by NDA as standard, and reflected in the client-facing transparency one-pager you get from the audit, the document you hand a client who asks what's AI-assisted in their work.
Whichever fits the task. We're model-agnostic across Claude, OpenAI and Gemini, and every recommendation comes with a projected monthly run-cost: model selection, usage caps, caching strategy. You get a clear number to approve before anything goes live, and a straight call on which model fits, with nothing riding on which provider you pick.
The parts clients pay you for. The brief, the judgement and the relationship belong to your people, at the front of every piece of work and at the back. We build the systems that compress the production middle: the rework, the reporting, the retrieval, the admin.
You do. Builds live in your accounts, and every build ships with documentation written so your team can run it without us. The retainer exists because most agencies want the systems maintained and governed, not because you're locked in.
Take the AI Operations Readiness Assessment and we'll send back your agency's score against comparable independents, the top three margin opportunities you're not yet capturing, and a 90-day outline. We only need email and agency name.
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Not ready for the assessment? Email us at daniel@daio.uk.