How accurate is the preview compared to the actual result?

Accurate enough to set realistic expectations, not a clinical guarantee. The render shows the most likely outcome based on the customer's photo and your category model. We bake a short disclaimer line into the preview UI so the customer understands it's a visualization, not a promise. Practices using it report fewer expectation mismatches at the chair, not more, because the conversation about "how close will it be" happens before the booking, not after.

Does the render run on the customer's phone or your servers?

Server-side. The customer uploads, our inference runs the model, the result comes back in 15–30 seconds. Phone-side generation isn't fast or accurate enough yet at photorealism levels. Server-side also means we can update the model without asking customers to update an app.

Which categories work best?

Categories where the buying objection is visual: dental aesthetics, hair colour and styling, cosmetic aesthetics, interior design, landscaping. Process-driven services (massage, oil changes, routine dental) see smaller conversion lifts because the booking decision isn't about how the customer will look. See the category section above.

Can we add custom outcome styles?

Yes. The default model ships with a category library. Most businesses then add 3–5 house styles trained on their own past work. A salon might add their three signature balayage tones. A dentist might add their preferred veneer shade range. That tuning is part of onboarding.

Is it HIPAA-safe for dental and medical use?

The platform is built to handle protected health information correctly: encrypted at rest and in transit, BAA available, no training on customer photos, configurable retention windows. If your jurisdiction adds extra layers (state-level dental regulations, EU patient data rules), we'll walk through the specifics on the call. We don't pretend compliance is one-size-fits-all.

How quickly can we go live?

Standard launch is 2–4 weeks. Week 1: category model selection and style tuning on your past work. Week 2: embed setup on your booking form or site. Week 3–4: a soft launch with a subset of traffic, then a full switch once preview-to-booking analytics look right. Faster if you don't need the custom style tuning.

Makeover – AI Before & After Preview Tool

Makeover

Show the result before they commit

Visit MakeoverSee case study

In short

Makeover is an AI tool that generates photorealistic before-and-after previews from a customer's own photo. Service businesses in dental, aesthetics, hair, interior design, and 40+ categories use it to show the result before clients book. Users report more same-session bookings.

The biggest barrier to booking a service isn't price. It's uncertainty. Clients want to know what they'll look like after the dental work, the hair colour, the renovation. Generic stock photos don't answer that question.

Makeover generates a photorealistic AI before-and-after preview on the customer's own photo in seconds. No design skills needed. Works across 40+ transformation categories: dental, aesthetics, hair, interiors, landscaping, and more.

Businesses using Makeover report fewer "I'll think about it" responses and more same-session bookings. Built because showing beats telling. The same approach drives our broader AI development work.

Why service businesses are switching

Customers don't ghost because of price. They ghost because they can't picture the outcome on themselves.

Before Makeover

Inquiry-to-booking sits around 18–22%
Stock photos look generic, not them
Consult calls eat 30 minutes explaining the change
Customers ghost after the first call

After Makeover

Same-session bookings jump to 35–40%
It's their face, their room, their result
Consult calls drop to 18–20 minutes
Inquiries convert before they cool off

In practice

A US cosmetic dentistry practice put Makeover previews on its website inquiry form. Same-session booking rate climbed from 22% to 38%. Average consult call time dropped from 32 minutes to 19. The receptionist stopped fielding "can you describe what veneers would look like on me." The form now sends the render with the lead.

Which service categories see the biggest lift

Honest answer: not all 40+ categories convert equally. The pattern is consistent. Wherever the buying objection is "I can't picture what I'd look like," Makeover lands hard. Where the result is process-based, the lift is smaller.

Categories that move the needle:

Dental aesthetics (veneers, whitening, alignment finishes). The buying objection is appearance-based and the customer has a clear "before" they already see in the mirror every day.
Hair colour and styling. High regret risk on colour changes. A render on the customer's own selfie de-risks the booking.
Cosmetic aesthetics (lip enhancement, brow shaping, non-surgical contouring). Visualization is the entire purchase decision.
Interior design and renovation. The homeowner is staring at the room they want changed. Showing the rendered version on their photo beats any moodboard.
Landscaping and exterior remodels. Same logic. The yard, on their phone, after the change.

Where the lift is smaller:

Massage, oil changes, dental hygiene, physiotherapy, and most maintenance services. The customer isn't booking based on how they'll look. They're booking based on how they'll feel or what was fixed. A render doesn't change the decision.

If your service sits in the second group, Makeover isn't the conversion tool you need. We'd rather say that than sell into a category where the math doesn't work. If you're not sure which bucket you sit in, book a 30-minute call and we'll tell you straight.

What Makeover actually does

Six pieces that turn an inquiry form into a same-session booking.

01
Own-photo upload
Customer uploads from phone or webcam. Render runs on their image, not a model's. The result is them, not a lookalike.
02
Side-by-side preview gallery
Original next to 2–3 outcome options. Lets the customer pick a direction before they ever speak to your team.
03
Embeds in your booking form
Iframe or web component. Drops into your existing site, lead form, or chatbot. No site rebuild.
04
Brand-safe styling
Output stays within the realistic range you set. No surprise stylization, no cartoony renders that embarrass your brand.
05
Category-trained models
We tune the generation model per business. A veneers practice and a landscaper don't share the same outcome library.
06
Preview-to-booking analytics
See which categories, styles, and outcome options convert. Your booking team gets a heat map, not guesswork.

Why teams choose Makeover

Four reasons that matter when the render lands in front of a real customer.

01
Photorealistic, not cartoon
Custom-trained per business on real outcome libraries. Most generative tools default to a stylized look that reads as filter, not result. Makeover doesn't.
02
15–30 second generation
Speed matters at the point of inquiry. A 5-minute render means the customer closes the tab. Ours finishes inside the attention window of an inquiry form.
03
Branded to your site
No Makeover watermark on the customer-facing render. The output looks like it came from your practice, not a third-party widget.
04
Built for booking conversion
This isn't a gallery showcase tool. It's a conversion layer for the inquiry-to-consult step. Every product decision optimizes for that.

When Makeover isn't the right tool

Three situations where we'll tell you not to buy it:

Medical claims that need regulatory sign-off. Some jurisdictions treat predicted clinical outcomes (orthodontic alignment, surgical results, dermatology before-afters) as regulated marketing. If your render needs formal medical review or a disclaimer the size of the image itself, the friction usually kills the conversion lift. Worth a conversation before you decide.
One-off transformations with no repeatability. Custom kitchens or commissioned art pieces, for example. The model needs a consistent outcome library to train on. If every job is fully custom, you're better off with a designer's hand-drawn moodboard.
Under 50 monthly inquiries. The ROI math gets thin. Below that volume, the per-render economics don't beat the cost of just doing a longer consult call. Come back when you're growing.

FAQs

: Accurate enough to set realistic expectations, not a clinical guarantee. The render shows the most likely outcome based on the customer's photo and your category model. We bake a short disclaimer line into the preview UI so the customer understands it's a visualization, not a promise. Practices using it report fewer expectation mismatches at the chair, not more, because the conversation about "how close will it be" happens before the booking, not after.
: Server-side. The customer uploads, our inference runs the model, the result comes back in 15–30 seconds. Phone-side generation isn't fast or accurate enough yet at photorealism levels. Server-side also means we can update the model without asking customers to update an app.
: Categories where the buying objection is visual: dental aesthetics, hair colour and styling, cosmetic aesthetics, interior design, landscaping. Process-driven services (massage, oil changes, routine dental) see smaller conversion lifts because the booking decision isn't about how the customer will look. See the category section above.
: Yes. The default model ships with a category library. Most businesses then add 3–5 house styles trained on their own past work. A salon might add their three signature balayage tones. A dentist might add their preferred veneer shade range. That tuning is part of onboarding.
: The platform is built to handle protected health information correctly: encrypted at rest and in transit, BAA available, no training on customer photos, configurable retention windows. If your jurisdiction adds extra layers (state-level dental regulations, EU patient data rules), we'll walk through the specifics on the call. We don't pretend compliance is one-size-fits-all.
: Standard launch is 2–4 weeks. Week 1: category model selection and style tuning on your past work. Week 2: embed setup on your booking form or site. Week 3–4: a soft launch with a subset of traffic, then a full switch once preview-to-booking analytics look right. Faster if you don't need the custom style tuning.

What clients say

Most clients stay.
Some say so on camera.

Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.

Dr.J. Ayo Akinyele

USA

President, Co-Founder

I was pleased with RaftLabs team's quality, consistency and execution.

01 / 14

Want to build something like Makeover?

Tell us what's not working in your business. We'll find the real problem and tell you exactly what it would take to fix it.

Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
All conversations are NDA-protected.