Sometimes the problem is not that a website is old.
It is that the knowledge of how it works left with the person who built it.
A good friend of mine has an online art gallery featuring Indigenous artifacts, paintings, carvings, and handmade jewelry. It was a massive collection of products available for purchase online, and the store had been live for well over a decade. Many of the pieces were personal and rare items collected over generations by Grand Chief Ronald Derrickson, which made the collection even more meaningful. This was not just inventory sitting on a shelf. It carried history, story, and value that could not easily be recreated.
The problem was that some of the staff who had once managed the site were no longer with the organization, and over time, key pieces of access and knowledge disappeared with them.
They were no longer sure how to get into the backend properly, update where order notifications were being sent, or manage important pieces of the site like inventory and operational settings. We tried every possible route to figure out some of the backend details, but answers were hard to come by. The person who had effectively held the key was gone, and no one else seemed to know where that key had gone with them.
Fortunately, I was able to gain enough access to redirect important notifications and help secure the site, but the larger problem was still sitting there.
The website was outdated. The team was not fully trained on the platform. They were not confident operating it. And even if we solved one issue, there was still a much bigger question underneath it all: was this really the right foundation to keep building on?
My recommendation was to move the site to a platform like Shopify. Not because every business needs Shopify, but because in this case the team needed something more user-friendly and more manageable. Inventory, payments, shipping, communications, and everyday updates could all live in one cleaner dashboard. It is widely used, easier to learn, and supported by a huge ecosystem of resources and tutorials.
But before any migration could happen, we had another problem to solve.
We needed the products. All of them.
Images, descriptions, tags, dimensions, details, and all the information required to rebuild the store properly. And with more than 800 products, this was not a small job. Under normal circumstances, you would ideally export that information from the backend. But since we could not get the level of backend access we needed, that option was off the table.
That is where a tool like Browse AI becomes incredibly useful.
Browse AI is built to scrape, monitor, and extract data from websites without code, including turning website data into spreadsheets, APIs, or automated workflows. The platform emphasizes point-and-click setup, website monitoring, and integrations with tools like Google Sheets and Airtable, which makes it especially practical when you need structured data from an existing site but do not have traditional backend access.
In a case like this, the value is obvious.
Instead of manually copying product after product, image after image, and detail after detail, a tool like Browse AI can help pull structured product information from the front end of the site so you have a working foundation for migration. It can also monitor pages, extract repeated data patterns, and export results into places where the team can actually work with them. Browse AI specifically positions itself around scraping data from websites, monitoring for changes, exporting to spreadsheets, and scaling extraction across many pages, which is exactly the kind of need that shows up in projects like this.
What I find especially useful about a tool like this is that it is not just for marketers or growth teams.
It can be a rescue tool.
When systems are old, access is messy, and business continuity depends on recovering what is still publicly visible, web extraction can become a bridge between where you are stuck and where you need to go. Browse AI also highlights prebuilt robots, no-code setup, monitoring, and support for extracting data from many pages at scale, which makes it much more realistic for large catalogs than trying to do everything by hand.
And that is the bigger lesson here.
A lot of organizations do not realize how vulnerable they are until one person leaves with too much undocumented knowledge. Credentials are missing. Processes are unclear. Systems are outdated. The business keeps running, but only barely, because too much of the operation was tied to individuals instead of shared understanding and accessible tools.
That is not just a website problem. That is an operational risk problem.
In this case, Browse AI would not replace the need for a proper migration plan, a cleaner ecommerce platform, or better internal documentation. But it could absolutely help recover and structure the product data needed to make the move possible. And sometimes that is exactly what a business needs most. Not a flashy AI use case, but a practical one. A tool that helps you get unstuck.
Because when the backend key is gone, sometimes the smartest move is to work from the front end instead.
Want more practical shortcuts like this?
Explore my curated library of AI tools, prompts, and workflows at resources.taneilcurrie.com