Layrs and Fora Soft logo

LAYRS – AI-Powered HDR Image Processing for Real Estate

Visit project
Arrow icon
Laptop screen showing split view of a living room makeover with 'Before' cozy beige sofa setup on the left and 'After' modern stylish seating area on the right.
Laptop screen showing text about transforming real estate photos instantly with AI and a button labeled Upload Photos.
Laptop screen showing a dark-themed interface highlighting benefits of LAYRS: faster property listings, higher buyer engagement, professional-grade results, and how it works with upload photos, AI enhancement, and download results steps.
LAYRS automates the creation of real estate imagery using advanced AI neural networks paired with a clean, intuitive interface. The platform generates vibrant, highly detailed photos that showcase every property in its best light, saving time while producing professional-quality results.
Flowchart with three steps: Upload Photos with upload icon, AI Enhancement with sparkle icon, and Download Results with download icon on a dark gradient background.
The Challenge
Manually creating HDR images is slow, requires technical expertise, and can bottleneck the speed of real estate marketing. Traditionally, photographers shoot three versions of a property: one underexposed, one overexposed, and one correctly exposed, and then merge them into a single, polished HDR image.

Our client wanted a way to automate this process while maintaining, and even improving, the quality of the final images.
Laptop screen showing text about transforming real estate photos instantly with AI and a button labeled Upload Photos.
Diagram showing three dim kitchen images linked to an AI box, leading to one bright, modern kitchen with white cabinets and stainless steel appliances.

Our Solution

We developed a fully automated AI-driven HDR solution that streamlines the entire workflow. Users simply upload three original photos to a web platform. The system automatically combines these images into a single HDR photo and then feeds it into a custom neural network for advanced color correction.
AI Training & Fine-Tuning
We trained and fine-tuned our own AI neural network specifically for this task, improving both color accuracy and overall image quality. The network continues to learn and adapt, allowing the client to further train it using original photos and final HDR results to enhance performance over time.
Side-by-side comparison of a house at night with the left half brighter and more detailed and the right half darker and less clear, with an 'Ai' icon in the center.
Laptop screen shows a side-by-side comparison of two modern living room interiors labeled 'Before' and featuring different furniture and decor styles under the heading 'See the Difference'.

Custom Training Interface

To make continuous improvement seamless, we created a dedicated interface for neural network training. The users can input original photos and corresponding HDR outputs, and the AI learns from each iteration, gradually improving color correction and overall image fidelity.
LAYRS transforms the way real estate professionals produce high-quality images. By automating the HDR process and integrating advanced AI for color correction, the platform saves time, reduces manual effort, and delivers consistently vibrant, detailed photos.
Website interface for LAYRS, a real estate photo enhancement tool featuring a before-and-after photo slider of a living room, icons for uploading photos, AI enhancement, and downloading results, plus reasons to choose LAYRS and a call-to-action button.

Looking to develop a similar AI-powered app?

Our team can build a tailored system that streamlines content creation, boosts productivity, and engages your users. Contact us today for a tailored quote.
Describe your project and we will get in touch
Enter your message
Enter your email
Enter your name

By submitting data in this form, you agree with the Personal Data Processing Policy.

Thumb up emoji
Your message has been sent successfully
We will contact you soon
Message not sent. Please try again.