CASE STUDIES
See how it works in practice.
Three recent projects. Different businesses, different problems, same approach.
How we helped a UK Plc unlock AI across a 240,000-asset creative operation
A large UK gaming company producing more than 240,000 marketing assets a year across multiple brands and channels. The business was shifting to a more automated and personalised marketing model. The in-house studio needed to increase output by 2–4x without sacrificing quality or burning out the team.
Previous advisors had spent months exploring tools and platforms without getting any closer to a workable solution.
We started with the work. We mapped how briefs, files, feedback, and approvals moved through the studio by talking directly to the people doing it. We also spoke to key tech partners to understand how their platforms could connect as part of a joined-up system.
We found a fragmented operation. Different teams, tools, and processes across brands and markets. Work scattered across systems. Automation and AI had nowhere stable to sit.
The leadership team came away with a clear blueprint for what a future creative operation would need to look like, and a shared language to discuss the trade-offs between quality, speed, and scale.
The work laid the foundation for partner conversations, investment planning, and the next phase of decisions around creative production and AI.
The studio was trying to solve two very different problems the same way. High-value campaign creative needs judgement and craft. Tens of thousands of repetitive variations were being built by hand. Speeding up the existing process would deliver marginal gains. They needed a new operating model.
“Previous advisors would focus on platforms and efficiency, but not on how the studio actually worked or what we needed to protect in quality and craft. This process nailed it. And it was fast – not the usual months of consultancy.”
Global Head of Brand
How we helped a boutique NY agency get a new business edge with AI
A fast-growing creative agency in New York. Clients include global sneaker, athletic equipment, and drinks brands. They were winning bigger briefs, but the team was stretched.
AI felt promising but unclear. They wanted it to make them faster and sharper without damaging their creative edge.
Over four months we took the whole agency through a mix of training, workshops, and consulting:
- Two full-day hands-on AI training sessions
- A workshop to identify real workflow blockages
- An audit of their tools, processes, and use cases
- A clear roadmap for where AI would make a real difference
- Support around production, including AI-native video partners from our network
Run through Woolf & Hale, our training practice.
AI moved from a side experiment to a core part of how the team worked every day. They used it to get up to speed on brands in hours rather than days, test strategic angles before committing to creative routes, and build stronger pitch responses.
The agency came in thinking AI would mainly help with creative output. The biggest gains were actually in new business speed, strategy and insight work, and less time lost to admin, proposals, and internal churn.
“One major global new business lead said it was the fastest they’d ever seen an agency get to know them and onboard. We won that pitch.”
CEO & Founder
How we helped a London agency build AI tools their own team could own
A creative production agency specialising in entertainment marketing. Major film studios, streaming platforms, and global gaming brands. A core team of around 20, scaling with freelancers on big campaigns.
The team was stretched. Briefs arrived late or unclear. Information was scattered across Slack, email, servers, and decks. Senior people spent their time firefighting.
Some individuals were already using AI. But there was no shared view of where it could help the business most – and no time to figure it out.
We talked to every department – production, creative, account management, new business, digital. Five sessions with the people doing the work. We found 18 opportunities, scored them in a prioritisation workshop with leadership, and built a 12-month roadmap.
Then we moved straight into four projects in parallel:
- New business early warning system – an automated pipeline from trade publications into a triaged Slack channel, with a named daily owner
- AI costing companion – a first-pass estimating tool that takes structured briefs through an LLM and returns costed estimates with visible assumptions
- Versioning tools evaluation – a structured assessment of three creative automation platforms, tested against a real campaign of 130 masters across 9 territories and 8 languages
- Server management – a full review of on-prem storage, cloud archive, backup gaps, and folder structures
The early warning system and costing companion were both built by two people from the client’s team – a domain expert and a systems generalist. We scoped it, wrote the implementation plan, ran the kickoff, and checked in weekly. The build was theirs.
The costing companion saved significant time on first-pass estimates and brought consistency to pricing. Better margins, fewer surprises.
The early warning system put the agency in front of the right clients at the right moment. Even one job won would pay for the entire engagement.
The versioning evaluation proved that the platforms on the market weren’t ready for their level of craft. A valuable answer that stopped the team chasing something that didn’t exist yet.
The server project turned out to be a process problem, not an infrastructure one. The team fixed most of it themselves.
Around a third of the recommendations had nothing to do with AI. Time tracking, content strategy, and late-stage change handling needed better systems – not smarter technology.
“We didn’t want a report that sat on a shelf. Within weeks of the audit we had four workstreams running with clear owners. Some of the answers weren’t even about AI – they were about fixing processes we’d been working around for years.”
Founder/CEO