Every enterprise CMS sale has the same awkward moment. The demo goes well. The prospect is engaged. The business case is solid. Then the implementation estimate lands on the table, and the room goes quiet.

We have lost deals because of the implementation cost. We have also won deals fixing those same implementations later.

Konabos has always been the team people call when an implementation goes sideways or when the existing partner cannot get it across the finish line. We know what these projects cost because we have been on both sides of the invoice. And we knew the math had to change.

Where the Time Actually Goes

When you break down a typical CMS migration or replatforming project, the work falls into a few buckets. There is architectural planning. There is the component development. There is the content migration and page assembly. And there is the QA cycle that follows all of it.

Most of that middle section, the content migration and page assembly, is labor-intensive but repetitive. A developer looks at the existing site. They identify the page structure. They map components. They recreate templates. They migrate content. They wire up data sources. They check rendering. They fix what broke. They do it again for the next page.

For a 25 to 100 page site, that process takes weeks. Sometimes months. It is not technically difficult work for a senior developer, but it is slow, and that slowness drives the cost that kills deals.

We saw this play out on a deal not long ago. The customer wanted Sitecore. The use case was clear. The strategy made sense. We came in with an implementation estimate around $500K, which covered a portal build, a full site migration, and the surrounding work. We were actually the cheaper of the two partners in the running. And we still lost the deal. Not because the platform was wrong. Not because the team was wrong. Because the implementation cost did not make sense to the business at that moment.

That loss stuck with us. Not because we did anything wrong, but because the underlying economics of implementation work made the right answer unaffordable.

What We Built and Why It Matters

We spent months building an AI-assisted migration tool that changes the economics of this work. Not by replacing developers, but by eliminating the repetitive assembly work that consumes most of a migration timeline.

The tool handles two primary scenarios. The first is taking any existing website, regardless of the CMS it runs on, and migrating it into Sitecore. That means templates, components, content, media, page layouts, all of it. The second is taking Figma designs and pushing them directly into a Sitecore instance using an organization's existing, approved component library.

In both cases, the tool does not generate new code. It does not hallucinate content. It does not invent components. It uses the existing content from the source site and maps it to a library of components that were hand-coded and reviewed by our senior front-end developers through multiple cycles of generation, code review, and refinement. The AI is stitching things together. The humans built the things being stitched.

The Numbers That Changed Our Thinking

When we first ran the full migration workflow end to end, we expected it to take about 45 minutes for a multi-page site. That includes analyzing the source site, mapping components, generating the page structures, running an initial gap analysis, pushing everything into Sitecore, and verifying that the result is page-editable by content authors.

It hit that target. A five-page site, fully migrated into Sitecore with proper templates, data sources, media library items, renderings, and page editor support, in under 45 minutes.

The Figma-to-Sitecore workflow was even faster. We expected 30 to 40 minutes per design. It took two minutes.

To put that in context, the traditional timeline for the same scope of work is 10 to 12 weeks. We are not talking about a marginal improvement. We are talking about a fundamental shift in what a migration project costs and how long it takes.

What This Does Not Replace

This is the part that matters most to us, and it is the part that differentiates this approach from the "AI will do everything" narrative that dominates most conversations right now.

Design, taste, and brand identity still need humans. The Figma workflow assumes a human designer already created the designs. We are not generating layouts from prompts. We are taking intentional design work and getting it into production faster.

Component quality still needs humans. Every component in our library went through seven to eight rounds of generation, code review, and refinement by senior front-end developers. The components are tested, accessible, and built on a framework (shadcn/ui) that Sitecore itself uses for its marketplace SDK. AI did not write the production code. Developers did.

Theming and brand alignment still need humans. After the migration runs, our front-end developers go in and tune the theme to match the brand precisely. That takes about a week. But a week of theming work on a site that is already fully assembled and functional in Sitecore is a fundamentally different project than three months of build-from-scratch work.

The gap analysis cycles still need human judgment. The tool runs automated checks for visual differences, content discrepancies, accessibility issues, broken links, and missing images. But a human decides which gaps matter and what the acceptable threshold is.

Why This Changes the Conversation

Speed is the obvious takeaway from those numbers. But speed is not the real story.

In most CMS projects, the majority of the budget is consumed just getting the site built. By the time the platform is live, there is little time or money left for the work that actually drives business outcomes. Personalization gets pushed to "phase two." Optimization gets delayed. Growth initiatives sit in a backlog. In many cases, phase two never happens because the budget is already gone.

That turns what should be a growth investment into a cost center. And when the C-suite looks at the next renewal or the next platform decision, all they see is a line item that consumed budget without demonstrating return.

When you compress the implementation from months to days, that dynamic inverts. Instead of asking leadership for budget to rebuild a website, you are asking for budget to grow the business. Instead of justifying cost, you are demonstrating return. Instead of a $500K implementation that takes three months, you are looking at a fraction of that cost and a timeline measured in days, not quarters.

That changes who in the organization cares about this conversation. It is no longer just IT evaluating platforms. It is the C-suite seeing a path from cost reduction to revenue growth to reduced risk, all in the same initiative. That is the kind of business case that gets funded without a fight.

The 80/20 That Actually Works

There is a version of AI adoption that is all sizzle. Vague promises about efficiency. Demos that look impressive but do not translate to production. Tools that generate 50,000 lines of code nobody can verify.

Then there is the version where AI handles 80% of the repetitive, well-defined work and humans own the 20% that requires judgment, taste, and accountability. Component quality. Brand alignment. Architectural decisions. Security review. Content governance.

That is the version we built. Not because it is the flashier story, but because it is the one that actually ships production sites that content authors can manage, marketers can personalize, and businesses can trust.

What Comes Next

For years, the limiting factor in CMS projects was effort. The platform could do more. The strategy called for more. But the hours required to get there ate the budget before the interesting work even started.

That constraint is starting to break.

The question is no longer "how long will this take?" It is "what do we do now that it doesn't take that long?"

That is a very different conversation.