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Let's Enhance

Let's Enhance is an company that develops deep learning-based tools for image enhancement, upscaling, and optimization, enabling users to improve photo quality for applications such as , , and .
Founded in 2018 by Ukrainian-American entrepreneurs Sofiia Shvets and Vlad Pranskevičius, the San Francisco-headquartered firm focuses on automating visual content processing to help businesses manage user-generated images efficiently.
The company's core technology leverages neural networks to perform tasks like increasing up to 16x without quality loss, sharpening blurry photos, restoring colors and lighting, and removing artifacts such as compression errors.
In 2021, Let's Enhance raised $3 million in seed funding led by Chamaeleon VC to expand its offerings, particularly for marketplaces seeking to scale visual content delivery.
Its primary products include the flagship Let's Enhance platform for general photo upscaling and image generation, as well as Claid.ai, a specialized suite for product photography that features -generated backgrounds, virtual models, and batch editing capabilities.
As of 2025, Claid.ai had been adopted by over 10,000 businesses, processing more than 200 million images, and the company continues to innovate in generative for visual workflows, including the launch of , a next-generation upscaler, in August 2025.

History

Founding

Let's Enhance was founded in 2018, with initial development beginning in late 2017 in , , as a startup focused on leveraging for image processing. The company was co-founded by Sofiia Shvets, who serves as CEO and brought prior experience from where she had worked for three years supporting startups and entrepreneurs, and Vlad Pranskevičius, a and practitioner based in . A third co-founder, Alex Savsunenko, was initially involved but departed shortly after to pursue other opportunities. The founders' initial motivation stemmed from Shvets' observations during her time at , where she identified a need for accessible, advanced tools to overcome the limitations of traditional photo editing software, such as manual upscaling that often resulted in loss of quality. Let's Enhance aimed to develop AI-driven solutions using super-resolution techniques to enable high-quality image enlargement, targeting both creative professionals seeking efficient workflows and everyday users looking to restore or enhance personal photos. As a Ukrainian-American venture, reflecting Shvets' background and Pranskevičius' local expertise, the early operations were centered in with a small team of three working from a space. The beta release of the core upscaling tool occurred in late 2017, offering a free online service powered by generative adversarial networks (GANs) and deep neural networks to process images without requiring user downloads or installations. This launch quickly attracted attention, leading to high traffic volumes that tested the nascent infrastructure, with the team providing round-the-clock support and forgoing salaries for the first six months to validate the . The service's emphasis on ease of use and automation marked it as an early entrant in the consumer-facing image enhancement space, setting the foundation for subsequent expansions.

Key milestones and funding

In September 2021, Let's Enhance launched Claid.ai as an end-to-end solution for automating image enhancement in , building on its consumer-facing origins. This was followed in October 2021 by a $3 million seed funding round led by investors including Chamaeleon VC, , Hype Ventures, and Acrobator Ventures, aimed at accelerating the development and scaling of Claid for marketplaces. This investment supported the company's transition toward enterprise-focused tools for and marketplaces. A significant expansion occurred in June 2022 with the release of Claid 2.0, a next-generation tool designed for scaling user-generated content optimization across multi-vendor platforms. The company has received backing from prominent accelerators, including and Google for Startups, which provided mentorship and resources to refine its AI imaging technologies. By 2023, Let's Enhance had grown its workforce to over 40 employees, maintaining operations across —where it was founded—and the , amid challenges from regional instability. By 2025, Claid.ai had been adopted by over 10,000 businesses and processed more than 200 million images. As of recent estimates, the company's enterprise value stands between $12 million and $18 million, reflecting its steady growth in the image enhancement sector without additional public funding rounds since 2021.

Products and services

Image enhancement tools

Let's Enhance provides -powered tools for upscaling and , enabling users to improve low-resolution or degraded photos without manual editing. The primary tools include the Upscaler and the Sharpener, which address common issues like , , and compression artifacts while supporting a range of creative and professional applications. The Upscaler increases image resolution up to 16x, transforming low-quality inputs into high-definition outputs such as , , or even 8K formats, with maximum sizes reaching 500 megapixels on business plans. It effectively fixes , , and artifacts by leveraging algorithms to reconstruct details intelligently, preserving natural textures and avoiding over-sharpening. For instance, users can upscale old family photos or AI-generated artwork from tools like , achieving print-ready quality at 300+ DPI without quality loss. This tool supports for up to 20 images at once, making it suitable for portfolios, landscapes, logos, and product visuals in . Complementing the Upscaler, the Sharpener focuses on enhancing overall image clarity for low-quality by adding intricate details, correcting color imbalances, and adjusting in a single operation. It offers one-click presets for quick professional results and capabilities, ideal for restoring portraits, landscapes, or product images that suffer from underexposure or noise. By boosting and sharpness, it prepares files for high-resolution at over 300 DPI, ensuring crisp outputs for applications like photography restoration or . The tool handles formats including JPG, PNG, and WebP, with free access limited to outputs up to 8 megapixels. New users receive 10 free credits upon signup, allowing initial testing without a , though outputs include a and are capped at lower resolutions like 8 megapixels for upscaling. Paid plans, starting from 100 credits per month, remove watermarks and unlock higher limits up to 512 megapixels, with unused credits rolling over on personal subscriptions. These tools integrate briefly with platforms via Claid.ai for automated enhancements, but primarily serve general creative and personal workflows.

Claid.ai

Claid.ai was introduced on June 21, 2022, as the second-generation tool from Let's Enhance, specifically designed as an end-to-end for marketplaces. It builds on the core upscaling technology of its predecessor to automate the enhancement of , aligning images with brand guidelines in seconds. This launch marked a shift toward specialized solutions for , optimizing over 100 million photos for major U.S. companies by launch. Key features of Claid.ai include automated capabilities such as resizing to fit requirements, background removal for clean product isolation, lighting adjustments to ensure optimal visibility, and variant generation to create multiple angles or styles from a single shot. These tools process images in formats like , , and , using industry-specific presets for sectors including , , and food to streamline workflows without manual intervention. The supports bulk processing via integrations with cloud storage like or Google Cloud, enabling teams to handle thousands or millions of images efficiently. Targeted at sellers and platforms such as and , Claid.ai addresses the need for consistent, high-quality product shots that drive sales, serving over 10,000 businesses since inception. It facilitates quick onboarding with no coding required for basic setups, allowing sellers to upload photos from public web folders or integrated systems for automated enhancements. In terms of performance, Claid.ai elevates to standards, preserving details while providing variable controls like and custom backgrounds for branding consistency, resulting in up to an 80% reduction in editing costs and up to 50% faster . Studies of adopting online shops show conversion rate increases of up to 20%, with improved visuals leading to higher purchase probability compared to subpar images. Recent additions as of 2025 include fashion models for try-ons and video generation for dynamic product visuals.

AI image generation

Let's Enhance offers an AI image generator tool that enables users to create original visuals from text prompts, transforming descriptive ideas into high-resolution . The tool utilizes advanced text-to-image conversion technology, where users input descriptions via a builder to generate images in various artistic styles. The generator supports a wide range of creative outputs, including realistic portraits, landscapes, drawings, paintings, , anime, and photographic styles, allowing for both photorealistic and abstract designs. Initial generations produce images at 2048x2048 pixels, which can be upscaled to resolutions up to 500 megapixels—equivalent to 125 times sharper than many standard tools—ensuring print-ready quality suitable for professional applications. This capability emphasizes greater detail, refinement, and realism in outputs, as enhanced in recent updates to the platform. Integration with Let's Enhance's enhancement tools allows seamless post-generation upscaling, where users can further refine and enlarge the AI-created images without loss of quality. For instance, the built-in upscaler can increase by up to 16 times, combining and enhancement in a single workflow. Common use cases include producing custom content for digital artists, such as , marketing materials like ad visuals and product shots, NFTs, and personalized portraits or landscapes, catering to creators seeking original, high-fidelity visuals.

Technology

Machine learning foundations

Let's Enhance's core technology relies on deep convolutional neural networks (CNNs) for image super-resolution, which are designed to restore details in low-quality photographs by learning patterns from extensive training data. These CNNs process images through layers that detect and reconstruct features such as edges, textures, and colors, enabling the addition of realistic pixels during enhancement. The models are trained on large datasets comprising hundreds of thousands of high-resolution real-world images, including both pristine photographs and artificially downscaled versions to simulate like compression artifacts. This training teaches the to recognize and replicate natural patterns, ensuring enhancements maintain clarity and authenticity without introducing unnatural artifacts. In the architecture, generative adversarial networks (GANs) are integrated to generate realistic details, where a creates enhanced images and a discriminator evaluates their plausibility against real data. This adversarial process improves the naturalness of outputs, particularly for complex elements like textures in portraits or product shots. Since its founding in , Let's Enhance has pursued an iterative development approach, regularly updating models to better handle diverse image types, from landscapes and old photos to products and . These refinements involve retraining on expanded datasets to address specific challenges, such as artifact removal in compressed images.

Super-resolution and enhancement algorithms

Let's Enhance employs super-resolution techniques that leverage generative adversarial networks (GANs) to reconstruct high-resolution images from low-resolution inputs. These algorithms predict and generate missing pixels by learning patterns from vast datasets of high-quality images, effectively "hallucinating" realistic details for objects and textures that were not present in the original. This approach surpasses traditional interpolation methods like bicubic scaling, which merely average surrounding pixels and often introduce blurring or artifacts, by instead creating plausible new content based on contextual understanding. The core upscaling algorithm in Let's Enhance utilizes GANs to perform multi-stage enlargements, processing images incrementally—for instance, achieving 4x resolution by generating 16 new pixels for each input pixel—to reduce cumulative errors and minimize visual artifacts such as or unnatural smoothing. This staged method supports enlargements up to 16x while maintaining detail fidelity, particularly for real-world images affected by or . Built on (CNN) architectures within the GAN framework, the system ensures coherent reconstruction across varying input qualities. In addition to resolution upscaling, enhancement processes address common degradations through specialized components integrated into the pipeline. Deblurring is achieved through the pipeline to remove or compression artifacts. is performed to balance tones and restore vibrancy, ensuring accurate representation of the original intent while mitigating issues like fading or oversaturation. To control output quality, the algorithms incorporate selection mechanisms that optimize for either natural preservation or enhanced artistic effects, dynamically adjusting parameters to avoid over-sharpening or excessive detail invention that could distort . This is facilitated by the adversarial training of GANs, where a discriminator evaluates generated outputs against ground-truth examples to select the most artifact-free result. In 2025, Let's Enhance introduced several new upscaler models as part of its ongoing innovations: the Ultra upscaler in for maximum and preservation, the Strong upscaler in for intensive of , , and on small images, and the Old Photo upscaler in for restoring and colorizing historical photographs.

Reception and impact

User reviews and adoption

Let's Enhance has garnered generally positive user feedback across major review platforms. On , it holds an average rating of 4.6 out of 5 based on 24 reviews, while reports a 4.5 out of 5 rating from 164 reviews. Users frequently highlight its intuitive interface and reliable performance in improving image without requiring advanced technical skills. The platform has achieved widespread adoption, with over 5 million users worldwide as of 2025, particularly among photographers seeking to upscale old or low-resolution images, sellers optimizing product visuals, and digital artists refining AI-generated content. Its appeal stems from features like one-click enhancement, which integrate seamlessly into creative and workflows. Common praises include the rapid processing speeds that deliver results in seconds, the natural appearance of enhanced images that preserve details without introducing artifacts, and the free tier's accessibility via 10 initial credits for testing. These elements have contributed to its popularity for both personal and professional use. Criticisms primarily revolve around the watermarks applied to outputs from the free tier after credits are exhausted and the credit-based pricing model, which can restrict access to high-resolution or without upgrading to a paid plan. Adoption has grown notably following the launch of Claid.ai, Let's Enhance's enterprise-focused extension, and the 2022 release of its , driving business applications and resulting in over 10,000 companies using the tools for automated image workflows, with more than 200 million images processed to date.

Industry recognition and partnerships

Let's Enhance has received notable recognition within the tech community, including strong performance on , where its initial launch ranked #1 of the day on November 4, 2017, and Let's Enhance 2.0 achieved #3 of the week on May 7, 2020. The company has also been backed by prominent accelerators such as , which supports its growth through mentorship and resources, as well as Nvidia's Inception program, designed for AI startups leveraging GPU technology. Additionally, participation in has provided cloud infrastructure and scaling support, enabling efficient deployment of its AI models. In terms of partnerships, Let's Enhance has collaborated with EFI to integrate upscaling into super-wide workflows, allowing print services to enhance image resolution without quality loss for large-format outputs. Through its Claid.ai platform, the company has formed integrations with platforms and marketplaces, automating image optimization to improve product visuals and site performance; for instance, a with demonstrated enhanced photo processing for faster scaling in online . These efforts extend to creative agencies, which utilize the tools for batch editing in design pipelines, and print-on-demand services benefiting from automated enhancements, including partnerships with companies such as and Mixtiles. The company's advancements in AI-driven visual media have been highlighted in tech publications, such as the , which covered its $3 million seed funding and role in automating photo editing for . Similarly, AIN.ua has recognized Let's Enhance for launching innovative like Claid's, which empower B2B image processing at scale, and for its contributions to generative in product . This recognition underscores its influence on making tools more accessible, thereby shaping competitors in the image processing sector by prioritizing scalable, automated solutions over manual workflows.

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