Renovating a bathroom can easily mean spending €10,000, €20,000 or more.
Yet customers are often expected to make that decision using surprisingly little information: a few tile samples, catalogue images, perhaps a floor plan and a considerable amount of imagination.
The situation is not much better for the contractor.
After the site visit, measurements need to be transferred, products researched, prices checked, individual items calculated and the quotation assembled. Several days may pass before the customer receives anything concrete.
A lot can happen during those days.
The customer asks another company for a quote. They start having doubts. They forget details from the original conversation. Or a competitor simply responds faster.
With our venture Badrenovo, we are building a different process.
The idea is that during the consultation, the customer should already be able to see what their own bathroom could look like, which products are being proposed and roughly where the selected configuration sits in terms of price.
That turns a conventional site visit into a much more concrete sales conversation.
The real problem is not generating attractive images
AI can already generate impressive interiors.
That alone does not solve much.
A beautiful rendering of a random bathroom is of limited value if the customer’s actual room has a sloped ceiling, an awkward window or a radiator exactly where the generated image has decided to put a shower.
For us, the real problem consists of three parts.
The customer needs to recognise their own room
A visualization becomes useful when it starts with the actual space.
The existing bathroom is photographed. AI changes the design, materials and products while attempting to preserve the important characteristics of the room.
The customer is no longer looking at a generic showroom.
They are looking at a possible version of their own bathroom.
That changes the nature of the consultation.
Design and price need to move together
A visualization without a price is still mostly inspiration.
A buying decision requires both:
What will it look like? And what will this version cost?
We therefore connect the visual configuration with structured product and pricing data.
If the customer changes the tiles, tap, vanity or another product, that decision should affect more than the image.
It should also update the underlying calculation.
This allows different options to be compared directly in the context of the customer’s own room.
The quotation should not start again from zero
The third part is less visually impressive but probably more important commercially.
Once a customer and consultant have made decisions together, those decisions should not have to be manually entered into another system from scratch.
Product selections, variants, project information and prices are already available digitally.
That information can be used to generate a structured basis for the quotation immediately.
Depending on the project, labour, measurements, technical conditions and individual items may still need to be reviewed or added.
But the employee is no longer starting with a blank document.
That is where much of the time saving comes from.
How the Badrenovo process works
1. Capture the existing room
During the site visit, the consultant photographs the existing bathroom using a smartphone.
The system uses this image as the starting point for the visualization.
The objective is not simply to create an attractive result.
Windows, doors, room proportions and other important existing elements should remain as consistent as possible so that the image remains relevant to the actual project.
2. Configure the bathroom together
The customer and consultant can then change materials, colours and products.
For example:
- different tiles,
- a different vanity,
- a walk-in shower,
- alternative fittings, or
- different furniture.
The idea is simple.
The customer no longer has to imagine how two samples might eventually look together.
They can see the option inside their own room.
At the same time, selected products and prices are reflected in the calculation.
The consultation becomes an interactive configuration process.
3. Turn the configuration into a quotation
By the end of the conversation, the system already knows a significant amount of what will later be needed for the quotation:
selected products, variants, prices, customer information and project parameters.
That data can be used to prepare a structured quotation automatically.
Depending on the complexity of the project, an employee can then review technical details, labour and quantities before the quotation is approved.
The objective is not to remove professional judgement from the calculation.
It is to automate the unnecessary part of it.
What sits behind the system
Badrenovo is not a single AI model.
It combines several layers.
Image generation
An image model creates design variants based on the existing bathroom.
The specific model is intentionally replaceable.
Image-generation technology changes extremely quickly. A serious product should not depend on one provider remaining the best option forever.
Product and pricing data
More important is the connection between the visualization and products that can actually be supplied.
Which tile is being shown? Which tap? What are the dimensions of the vanity? What does the product currently cost?
Those answers should not come from an AI model guessing.
They come from structured product and pricing data.
This is where we believe much of the long-term value sits.
A generic AI model understands the general market.
A business system should understand your products, your prices, your rules and your historical experience.
Workflow and calculation
The final layer connects everything.
The system needs to know which products belong to the selected visualization, which information goes into the calculation and what eventually appears in the quotation.
These workflows are much less visible than the rendering.
But they determine whether a nice AI demonstration becomes something people can actually use in front of a customer.
Why speed matters in sales
A lot of digitalisation in the trades begins after the order has already been won.
Time tracking becomes digital. Invoices are automated. Project documentation moves into an app.
All of that is useful.
But none of it helps win the customer in the first place.
With Badrenovo, we are especially interested in the part before the signature.
How quickly can the customer understand what they are buying? How quickly can they understand the price range? How easily can they compare different options? And how much time passes between the consultation and receiving something concrete?
If technology can reduce that delay from several days to hours or even minutes, it affects more than administrative efficiency.
It affects sales.
The lesson is bigger than bathrooms
Badrenovo is designed for bathroom renovation.
The underlying pattern applies much more broadly.
Move information into the decision moment
Almost every sales process contains something the customer has to wait for: a visualization, a calculation, a feasibility check, a delivery estimate or a technical assessment.
The interesting question is:
Can that information be produced while the customer is still in the conversation?
If it can, the sales process changes significantly.
Use the data only your business has
Generic AI models are available to every competitor.
By themselves, they are therefore unlikely to create a lasting advantage.
Proprietary business data is more interesting: price lists, product information, historical quotations, project images, calculation rules, delivery times and experience from previous jobs.
When those data are structured and connected intelligently to AI, the resulting system becomes much closer to how the actual business works.
Automate revenue, not only administration
A common automation question is: “How can we reduce work after winning the project?”
There is another question worth asking:
“How can we sell faster and better before the customer signs?”
That is where we see some of the most interesting AI opportunities for established businesses.
We build these systems ourselves first
Badrenovo is not a theoretical consulting concept from Bergstone.
It is one of our own ventures.
We develop the visualization pipeline, product logic, data structures and quotation workflows ourselves, which means we see directly what survives contact with real users and what does not.
That matters.
There is a surprising amount of invisible work between an impressive AI demo and a tool an employee can reliably use in front of a customer.
The response time has to work. Products need to be matched correctly. Prices need to be traceable. The system needs to deal with imperfect photographs. And employees need to understand what has been automated and what still requires professional review.
Only then does technology become a business process.
Frequently Asked Questions
Does AI replace the bathroom designer or contractor?
No. The system supports consultation, visualization and quotation preparation. Technical decisions, final measurements, feasibility checks and approval of the quotation remain with qualified people where professional judgement is required.
Is the visualization technically binding?
No. AI visualization is primarily a tool for communicating design ideas and product options. It does not replace technical planning, construction drawings or a binding feasibility assessment.
Does the visualization preserve the geometry of the existing bathroom?
That is one of the main objectives of the workflow. The source image and additional room information are used to keep important geometry and existing elements as consistent as possible. Generative image models can still introduce deviations, which is why we clearly distinguish between a sales visualization and technical planning.
Is the quotation calculated from a single photograph?
No. The photograph is the starting point for visualization, not the sole basis for pricing. A reliable quotation may also require measurements, product data, labour, existing installations and project-specific conditions.
Where do the product prices come from?
Prices come from structured product and supplier data integrated into the platform. This allows the calculation to work with actual products rather than asking an AI model to estimate their cost.
What happens when a material price changes?
Product and pricing data can be updated independently from the image-generation model. This separation is one of the reasons we treat visualization and calculation as distinct technical layers.
Can the system visualize things other than bathrooms?
Badrenovo itself is specialised in bathrooms. The underlying architecture can be applied to other products and services where visualization, configuration and pricing need to work together.
What types of businesses could use a similar approach?
The model is particularly relevant to businesses where customers need an individual design or calculation before buying. Examples include renovation, interiors, kitchens, furniture, façades, windows, landscaping and other configurable products or services.
Do we need perfectly structured product data first?
No. But the quality of product and pricing data determines how far the process can be automated. For many companies, one of the first steps is therefore to structure existing data and connect information that currently lives in different systems.
How quickly can a quotation be produced?
That depends on the project. For relatively standardised work, a significant part of the quotation can be prepared during or immediately after the consultation. More complex projects still require technical review and individual additions. The important difference is that information already captured during the consultation does not have to be entered again from scratch.
Can this connect to our existing software?
In many cases, yes. Product databases, CRM, ERP, calculation systems, scheduling tools and document-generation software can often be connected through APIs or custom integrations. The right architecture depends on the systems already in place.
The most interesting process may happen before the signature
AI integration is often discussed almost entirely in terms of efficiency.
That is useful, but incomplete.
Sometimes the more interesting question is not: “How can we do the same work more cheaply?”
It is: “How can we give the customer enough information to make a decision sooner?”
That is what we are exploring with Badrenovo.
Visualization, configuration and calculation are no longer treated as three separate tasks, but as one connected process.
And that leads to the broader lesson:
A useful AI system does not start with the question of which model to use.
It starts with the question: Which moment in the existing business process should become better?
More about Badrenovo: badrenovo.de