No one got into fashion to rename files and update PLM.
We got into it to craft a fit, build a collection, develop the most inspiring brand. Working in fashion means making decisions at a constant pace.

Along the way, tools multiplied: data in PLM, Miro for reviews, AI that turns sketches into real product, 3D that makes sampling better. All of it is genuinely exciting. But when tools aren’t connected, more and more time is spent moving files and data from one system to another.

When you decide to integrate, where do you start? If anything is possible, what makes most sense?

That’s what we built the Workflow Assessment for. Most consultants prove value after implementation. We bring you proof upfront. We have years of experience connecting tools across fashion brands - which means we can model what happens when your tools talk to each other before you commit to building anything.

In just two weeks, we scan your tech landscape and the way you work, and hand you the plan, the impact, and the numbers behind it.

We get you the numbers, you make the call.
We’ve got the expertise to deliver on what we find.

It runs in three phases. We set the goal together, so measurement has a target. We follow your team and measure real workflow, not documented process. We find where the friction lives, where focus breaks, where time disappears every season, silently, because two tools that should talk to each other don't. Then we model what happens when they do.

Questions we hear a lot

Can we build this internally?
You can map a process. What we bring is years of cross-brand implementation. We know what works, what breaks, and what things cost in practice. The scenarios we build are grounded in that. You’re not paying for theory.

We’ve already mapped our process. Do we still need this?
A process map tells you what happens. The assessment tells you what it costs, where the real friction is, and what changes when you fix it. Most brands we work with have documentation. Very few have impact data.

What do I walk away with?
A friction heatmap of your tech stack. ROI modeling for each automation scenario. A prioritized roadmap with implementation timelines, specific enough to take into a budget conversation on day fifteen.

Can we get started right away? How long does it take to deliver?
Book a call and we'll get you booked in. At the end of the assessment, we build a phased plan around your reality. Once you sign it off, we get started. We have frameworks for most integrations. That means weeks, not months.

Less manual work
Workflow that sticks.
& business model that scales.
Every season

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Making it scale across a team, a company, or a season that’s where the hard work begins.

The question is how do you make it follow brand consistency without burying your team in an endless maze of prompts. How do you turn AI from a tool into a workflow.

And honestly, this is nothing new. We’ve been here before with 3D, and before that with setting up the Adobe suite. We all want to believe we can skip the structure and go wild. And to some extent you can. AI turns every detailed instruction, design direction, or reference image into something beautiful.

The question is how do you make it follow brand consistency without burying your team in an endless maze of prompts. How do you turn AI from a tool into a workflow.

Manual prompting alone breaks

Prompting feels productive because the first results are surprising.

The trap is that it doesn’t scale. As soon as ideas become product it need refinement and control. Doing that with manual prompting can take hours and makes you want to pull your hair out.

Multiply that across a season and you don’t have a workflow and you have a very expensive digital photoshoot with an unpredictable timeline and unpredictable outcomes.

After running multiple rounds of ecom AI delivery for brands, we kept hitting the same wall. Not every brand had good structured input. No fit library, no material library, no label references. And the design input - usually an Illustrator file - made things worse. Those outlines were never set up as AI input. They’re artist impressions with drawn-on shadows and decorative details that confuse the model and distort the whole process.

What we realised is that AI needs structured data to work consistently. We started to call it Brand DNA. A mix of design library, dev library and brand guidelines, structured for AI use.

A Brand DNA layer fixes this by removing the part of the process that currently lives inside someone’s head. The brand becomes structured input, not a prompt users have to remember.

How we set up the Brand DNA

The funny thing, in most cases the Brand DNA already exists. It’s just not structured yet.

Almost every fashion brand is sitting on the main input layer they need. Their ecom images. Thousands of frames, shot to a tight standard, season after season. The lighting, the framing, the labels, the finishing, the fit. The small consistencies that make a product read, instantly, as yours.

Instead of treating it as output, we use it as input to build the Brand DNA structure.

We’re currently building this for one brand, Stieglitz. It’s early work, but what we’re learning is already changing how we think about AI input. We look at their existing imagery, identify the repeatable patterns - the ones a human eye recognises without thinking. The ones a model needs spelled out and wire them in as the input layer for their AI workflow. We’re now turning this process into a repeatable workflow so we can bring it to every brand we work with.

Consistent Brand DNA input gives us the data to generate consistent output. It’s not perfect yet, but with every model improvement, including the latest OpenAI image generation, the dataset becomes more valuable.

The point is not to make AI generate one good image. The point is to make it generate the hundredth one without anyone starting from zero.

That’s the difference between a tool and a workflow. A tool gives you an output. A workflow gives you consistency.

Build the structured input layer first. Then plug in whatever AI tool you like, we have no stake in any of them. We work with what you’ve got.

Recently, for one of our clients, we again deployed our CLO-SET render automation.

On the surface, it’s just controlling the start and the completion of the render process that’s happening inside CLO-SET. However, as a part of the full workflows, it really ties everything together, also by leveraging our external render dashboard.

The automation is simple but efficient. Works with these features:

• Track the user request to render

• Creates the request to render on CLO-SET with the user render preset (quality/resolution / etc.)

• Monitors the rendering process

  • Dashboard represents all triggered renders, their progress and statuses

• Upon completion of the rendering, the automation will download the rendered assets, rename them if required, and upload them to the destination systems (DAM / PLM / etc.).

  • Yet again, the dashboard reports the status of these operations

Each line monitors the “full circle” of the style during rendering:

• Start of the render with the direct link to the style on CLO-SET

• It’s progress

• Completion (or Failure - then will also leave a comment if it’s known why it failed)

• Status of DAM upload (or the system of your choice)

• Status of SharePoint upload

This automation can be easily deployed to any company using CLO-SET. Upload integrations are easily extensible to other systems, and the dashboard can also be adapted to your needs and branding if needed.

Get In Touch

L.L.Bean had invested heavily in Digital Product Creation. The 3D capability was strong. But as adoption scaled, a quieter problem emerged - designers were spending significant time on work that wasn’t design.

Renaming files. Re-exporting assets. Moving content between tools. Small tasks, but constant ones. Consistency suffered, adoptions slowed down.

The Challenge

Scaling 3D meant the manual overhead scaled with it

Scaling 3D across more categories meant the manual overhead scaled with it. File sizes grew. Handoffs multiplied. Most delays weren’t coming from rendering, they were coming from everything around it.

Designers lost momentum switching between tasks. Leadership couldn’t trust that the right assets were in VibeIQ at the right time. The workflow needed to change.

What We Found

The time study surfaced what everyone suspected but hadn’t quantified

EnhanceThat ran a workflow assessment with L.L.Bean's Digital Product Creation and Product teams. Saving, renaming, re-exporting and moving files was consuming far more time than rendering itself.

The cost wasn't just hours.
Every context switch broke creative momentum.
The case for automation was immediate.

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The Approach

One pipeline. Built around how the team actually works.

EnhanceThat built a seamless pipeline connecting CLO, product data and VibeIQ — designed around how L.L.Bean’s designers and product teams actually work.

Manual handoffs were removed. Naming, exporting and syncing happen automatically. The workflow is fully implemented within L.L.Bean’s environment and built to evolve as tools and requirements change. EnhanceThat continues to support it over time.

The Impact

Numbers that changed the conversation

• From 5+ minutes to 16 seconds — 95% faster

• High-quality images in 7 clicks — 84% less clicking

• Designers spend more time designing, less time managing files

• Assets are consistent across the workflow, with a shared visual language

• VibeIQ receives clean, structured data and the latest 3D assets

• Rework drops. Confidence in the pipeline goes up.

Why L.L.Bean Chose EnhanceThat

Everyone spoke the same language from day one

What It Unlocked

• Manual file handling has been removed from the core 3D workflow

• Disconnected tools now run as a single reliable pipeline

• Designers are designing more and managing less

• Digital Product Creation is positioned to scale across every category

A visual line plan. Styles and data connected in one overview everyone can access.
So basic. So essential. And for so many teams, so painful to maintain.

Our workflow assessments consistently show the same thing: the line plan is one of the biggest sources of manual work in a fashion company. Not because it’s complex. Because the tools aren’t connected.

Export images, download, rename, paste repeat. Every season and with every update made.

We built a connector that pulls images and data from PLM, CLO-SET, DAM - whatever source you’re working from. It drops them into the line plan, consistent and with the data you want to see. Miro happens to be where most fashion teams already work, so that’s where we built it. No extra tools to introduce. Just connect what you have.

It’s one of those cases that reminds me why we do this. We’re not building another tool. We’re making the tools you already have work better together.

Simple. And it solves one of the main friction points we see repeatedly in our workflow assessments.

A designer finishes a style in CLO. The render looks great. The work is done, you might think. This is where for many the least interesting part starts: saving, renaming files, and uploading them into different systems.

This is one example from one brand running thousands of styles a year. But it’s not limited to that brand, or to teams working in 3D. We see the same pattern everywhere - whether you design in Illustrator, with AI, or in CLO. Digital design tools create excellent output, but how much your company benefits from it fully depends on how well your tools and data are connected.

Turn tools into a workflow

There is no one-size-fits-all. Every team has a different calendar, different naming conventions, different places to store assets, and yes, different habits. To fully understand where automation can have the most impact with the least effort, we measure the workflow. We follow individual users, see where they click, what tasks they do manually, and ask where they experience the most friction. That heatmap tells us where we can have most impact.

FOCUS

As you might already sense, most of the friction sits in the handover between tools. That’s where users experience the most disruption. And honestly, why would a designer or merchandiser need to become an expert in naming conventions, render settings, or prompt writing?

One of the most powerful tools in our toolbox is FOCUS. It sits at the centre of the workflow and links tools based on brand milestones and context. At the point of saving a design from Illustrator, CLO, or any AI tool, the user gets a simple pop-up asking for the season, style data, and milestone. Based on your workflow, FOCUS takes over everything you would normally do manually. Saving, naming, rendering, combining AI and 3D, sending images and data to PLM or DAM. All in one click.

What got connected

CLO feeds into FOCUS. FOCUS triggers CLOSET. CLOSET pushes to PLM. PLM syncs to Miro. The automation layer handles the data flow, formatting, enriching, and delivering to each tool with exactly the right context, every time.

No manual export or navigation required. And when you decide to change tools the automation can easily be adapted even without changing the user experience.

The impact

85% reduction in manual work. Not from replacing the tools. Not from buying something new. From connecting what was already there and removing the steps that shouldn’t exist. The designers didn’t change how they work in CLO. They just stopped doing everything that came after it.

This is what a workflow assessment gets you

A workflow assessment doesn’t only show you where you can have the most impact, it also saves you building integrations that won’t pay off. Our model has been developed and tested with large enterprise teams, and gets more reliable with every engagement. We map it before we build anything. That’s always the order.

First we find where time is lost. Then we identify what should connect. Then we build the automation that makes the manual work disappear.

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On the FERMAT Podcast - why digital transformation stalls at the point of decision, and what it takes to connect product data, digital creation and AI into infrastructure that actually holds.

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