Custom AI Systems for eCom

If you run a business that depends on listings — whether that's 500 used cars on AutoTrader, 12,000 SKUs on Shopify, 40,000 rental properties on Zillow, or a million classified ads on your marketplace — you already know the dirty secret nobody wants to talk about:

Most of your listing images are bad. And bad images don't just look unprofessional. They actively cost you sales, every single day, on every single listing.

We built an infrastructure that fixes this. Not one photo at a time. Not with a team of freelancers in Photoshop. We enhance your images and rewrite your descriptions programmatically, at whatever scale you need, using the same AI systems that power the world's largest visual platforms — and we do it at a price point that would make your CFO smile.

Here's how it works, why it matters, and what the actual numbers look like.

The Problem Nobody's Solving Well

Every industry that relies on listings faces the same fundamental challenge: the gap between how a product or property actually looks and how it appears in its listing photo is costing real money.

Think about the last time you scrolled through a used car site. Some vehicles look like they were photographed during a hurricane in a junkyard parking lot. Others look like they belong in a magazine. Both might be the same year, same make, same model, same condition. But you clicked on the second one, didn't you? So did everyone else.

This isn't a small effect. It's massive. And it compounds across every listing in your inventory.

The core issue is that most businesses have listing images that suffer from some combination of the following problems:

• Inconsistent lighting (some bright, some dark, some blown out)
• Cluttered or distracting backgrounds
• Low resolution or visible compression artifacts
• Poor white balance that makes products look off-color
• No standardization across listings, so the catalog looks disjointed
• Descriptions that were either copy-pasted from a manufacturer spec sheet or written by someone in a hurry

When you've got a few dozen listings, you can fix this by hand. When you've got a few thousand, it's painful but possible. When you've got tens of thousands, hundreds of thousands, or millions? You're either spending a fortune on manual editing or — more likely — you're just living with it and bleeding revenue.

That's where we come in.

What We Actually Do

Let's be clear about what this is and what it isn't.

We are not generating fake photos. We're not putting your Honda Civic in front of a CGI waterfall. We're not creating fictional product images or misleading representations of your listings.

What we do is take your existing listing photos and make them dramatically better while keeping the subject matter completely authentic. The car is still the same car. The apartment is still the same apartment. The product is still the same product. But now it looks like a professional photographer lit it, shot it, and processed it — because our systems do the computational equivalent of exactly that.

Image Enhancement

Here's what happens when a listing image runs through our pipeline:

Resolution and sharpness. Low-res photos get upscaled intelligently. Soft images get sharpened. If your product photos were taken on a phone camera in 2019 and uploaded as compressed JPEGs, we can bring them up to a quality level that holds up on a 4K display with zoom functionality. This isn't the "enhance" button from bad TV crime dramas — this is genuine computational super-resolution that reconstructs detail based on learned patterns from millions of high-quality images.

Background cleanup and normalization. This is the big one for a lot of businesses. If you sell products, your images might have 47 different background colors, textures, and environments because 47 different people photographed 47 different items on 47 different days. We normalize these backgrounds. White backgrounds for product shots. Clean, uncluttered environments for real estate interiors. Consistent sky replacements for exterior property shots. The key word here is consistent — when a buyer scrolls through your catalog, every listing looks like it belongs to the same professional brand.

Color correction and white balance. A blue-tinted product photo makes even a gorgeous item look cheap. We correct white balance, normalize exposure, and ensure that colors look true-to-life across your entire catalog. This matters more than most people realize — studies in consumer psychology consistently show that accurate color representation reduces return rates and increases buyer confidence.

Composition adjustments. Cropping, straightening, and centering. If someone uploaded a listing photo where the product is crammed into a corner with a thumb visible at the edge, we fix that. The subject gets centered, the framing gets tightened, and the image goes from "garage sale" to "curated storefront."

Description Enhancement

Images are only half the equation. Your listing descriptions matter too — both for conversion and for search visibility.

SEO-optimized rewrites. We take your existing descriptions and rewrite them with proper keyword integration, natural language structure, and the kind of specificity that search engines reward. A listing that says "nice apartment, good location, 2BR" becomes a description that includes neighborhood names, nearby landmarks, square footage, specific amenities, and long-tail keyword phrases that people actually search for.

Structured data markup. For web-based listings, we can generate schema markup that helps search engines understand exactly what your listing contains. This means rich snippets, better click-through rates from search results, and more visibility across Google, Bing, and vertical-specific search engines.

Consistency and brand voice. If you have 10,000 listings written by 30 different people over five years, the tone probably ranges from "legal document" to "text message." We normalize the voice so every listing reads like it was written by the same capable professional on the same day.

The Numbers Are Staggering (And They're Not Ours — They're Industry Data)

We're not going to hit you with vague promises about "boosting engagement." Here's what researchers, platforms, and industry bodies have actually measured, broken down by vertical.

E-Commerce

The data on product image quality and e-commerce conversion is some of the most well-documented in all of digital marketing.

A frequently cited Shopify study found that products with professional-grade photographs convert at a rate roughly 33% higher than products with low-quality images. That's not a marginal improvement — that's a third more sales from the exact same traffic.

But it gets wilder. An e-commerce analytics compilation found that high-quality product photos had a conversion rate 94% higher than low-quality photos. In practical terms, the same item can sell nearly twice as well when presented with excellent images versus mediocre ones.

There's also the engagement side: about 75% of online shoppers rely primarily on product photos when making purchase decisions, and roughly 9 out of 10 consider high-quality images one of the most important factors in whether they buy or not.

Research from eBay's marketplace data showed that even the number of quality images matters at the listing level. Going from zero photos to one doubled the conversion rate. Going from one to two doubled it again. And a separate study found that a 28% increase in image size alone (not even quality — just display size) led to a 63% increase in conversions.

If you're running a store with 10,000 SKUs and your average product image is "fine but not great," you are almost certainly leaving 20-40% of your potential revenue on the table.

Auto Dealerships

The automotive vertical is where this gets really tangible, because the dollar values per unit are so high.

CDK Global's data shows that close to 90% of car shoppers are influenced to begin their buying journey based on the quality of photos on a dealer's website. Not reviews. Not pricing. Photos.

Dealer.com research found that new car listings with actual (non-stock) photos are 30% more likely to generate a lead. For used and certified pre-owned vehicles, that number jumps to 40%. And when visitors actually interact with photos on a vehicle detail page (VDP), they're 16% more likely to submit a lead compared to visitors who don't.

There's a consistency effect too. On dealer sites where more than 65% of inventory features real photos, customers spend about 5% more time on the site and view roughly 20% more vehicle detail pages. That's more eyeballs on more cars, which means more leads, which means more deals.

Consider the math: if you have 400 vehicles on your lot and upgrading your photo quality generates even 10% more leads, and your closing rate stays constant, that's 10% more cars sold. At an average gross profit of $2,000–$5,000 per unit, that's serious money — from photos alone.

And here's the kicker for dealers: CDK's own data shows it costs roughly $50 per day for every vehicle that isn't properly merchandised on your website. That cost adds up fast across an inventory of hundreds of cars sitting on the lot longer than they need to.

Real Estate

The real estate data is arguably the most dramatic.

A Redfin analysis of more than 100,000 listings found that homes with professional-quality photographs sold for between $934 and $116,076 more than comparable properties shot with point-and-shoot cameras. The exact premium depended on the price tier, but the effect was consistent: better photos correlated with higher sale prices across the board.

Properties photographed professionally sell about 32% faster. That translates to an average of 89 days on market versus 123 days for properties with amateur photos — a difference of over a month. For a seller paying a mortgage, taxes, and insurance on a vacant property, that month of carrying costs can easily run into the thousands.

Listings with professional images get 61% more views online. And according to VHT Studios' analysis of over 200,000 real estate listings, professionally photographed properties saw a 47% higher asking price per square foot.

The National Association of Realtors reports that 89% of homebuyers cite photos as the most important factor when browsing listings online. Not the description. Not the price. Not the neighborhood. The photos.

For agents and brokerages managing large portfolios of listings, the implication is clear: every listing with subpar photos is actively underperforming — selling slower and for less money.

Hospitality and Short-Term Rentals

Airbnb's own data has shown that properties with professional, verified photos are booked 2.5 times more frequently than those without. That's not a small edge — that's 150% more bookings.

Separate research indicates that Airbnb listings with professional photographs see up to 40% more bookings and can command higher nightly rates. On the flip side, properties with visually subpar listings earn an estimated 15–25% less per night than well-photographed competitors.

A Cornell Hotel School study found that 82% of travelers believe the quality of accommodation photos reflects the host's trustworthiness and the expected quality of their stay. So bad photos don't just cost you bookings — they undermine the trust you need to charge premium rates.

For property managers handling dozens or hundreds of short-term rental units, the math is straightforward. If upgrading photo quality across your portfolio moves your average occupancy rate up even 5–10 percentage points, that's tens or hundreds of thousands of dollars in additional annual revenue.

Restaurants, Food, and Delivery

This vertical has some of the most actionable data because the feedback loop is so tight — better photos lead directly to more orders.

Grubhub's data shows that restaurants with photos and descriptions on their menu items receive up to 70% more orders than those without. That's nearly double the order volume, driven entirely by visual presentation.

The same data set found that menu photos and descriptions increased sales by as much as 65% for restaurants that adopted them. Deliveroo's own research found that having specific images for each menu item increased conversions by 6.5%, and that Deliveroo's algorithm automatically ranks restaurants with hero images higher in search results.

Limetray documented a 25% increase in conversion rates when restaurant websites were updated to include food photography. And multiple industry studies converge on the finding that restaurants using photo-equipped menus see 20–30% higher sales compared to text-only alternatives.

For restaurant groups, dark kitchens, and multi-location chains managing hundreds or thousands of menu items across multiple platforms (their own website, DoorDash, Uber Eats, Grubhub, Yelp), consistently high-quality food photography across every item and every platform is a logistics nightmare when done manually. It doesn't have to be.

Classifieds and Marketplaces

Marketplace platforms face a unique version of this problem: they don't control the quality of images their sellers upload. And bad seller images drag down the entire platform's perceived quality.

Research published in the proceedings of the ACM International Conference on Web Search and Data Mining found that image quality is a reliable predictor of sales success on platforms like eBay, particularly in visual categories like apparel. The study also confirmed what we see empirically: listings with at least one photo double their conversion rate compared to text-only listings.

A study from the IEEE Winter Conference on Applications of Computer Vision found that image quality directly predicts trust in peer-to-peer marketplaces. Higher trust leads to better engagement and more transactions. The researchers found that users strongly prefer images with a large, clearly visible main subject, warm colors, high contrast, and depth-of-field — all characteristics that can be computationally applied to existing images.

For marketplace operators, this is a platform-level opportunity. If you can automatically enhance every seller's images on upload, you improve the conversion rate of every listing on your platform simultaneously. That's a systemic revenue multiplier.

How the Pipeline Works (Technical Overview)

For the technically curious — or for the CTO who's going to ask — here's what's actually happening under the hood.

Step 1: Ingest and Analyze

Your images come in via API, bulk upload, or direct integration with your existing platform (Shopify, WooCommerce, your custom CMS, your MLS system, your inventory management system — we've worked with most of them).

Each image gets analyzed for:

• Current resolution and compression level
• Dominant colors and white balance offset
• Background complexity and type (solid, outdoor, indoor, cluttered)
• Subject detection and bounding box
• Overall quality score on a 0–100 scale

This analysis determines which processing steps each image needs. A well-lit product photo on a slightly off-white background might only need color correction and background normalization. A dark, blurry smartphone photo from 2018 might need the full pipeline.

Step 2: Enhancement

Based on the analysis, each image passes through the appropriate enhancement stages. The pipeline is modular — we don't apply a one-size-fits-all filter. Each image gets exactly the processing it needs and nothing more, which keeps costs low and avoids over-processing.

The enhancement stages include:

• Super-resolution upscaling for low-res source images
• Intelligent sharpening that enhances detail without introducing artifacts
• Background segmentation and replacement using state-of-the-art segmentation models
• Color correction and white balance normalization based on the detected subject type
• Exposure and contrast optimization to ensure consistent brightness across all listings
• Automatic cropping and composition to center the subject and remove distracting edge elements

Step 3: Description Processing

Simultaneously — because why wait? — your listing text runs through our language pipeline.

For each listing, we:

• Analyze the existing description for completeness, keyword density, and readability
• Generate an enhanced version that preserves all factual information while improving SEO targeting, readability, and persuasiveness
• Optionally generate structured data (schema markup) for web-based listings
• Flag any listings with missing critical information (no price, no dimensions, no location) so your team can fill in the gaps

Step 4: Quality Assurance

Every processed image runs through an automated QA check before delivery. This catches edge cases where the enhancement pipeline might have done something unexpected — a background removal that clipped part of the product, a color correction that shifted a critical brand color, a crop that cut off important label text.

Images that fail QA get flagged for human review rather than pushed to production. We'd rather deliver 99% of your images in an hour and flag 1% for a quick manual check than push 100% with no safety net.

Step 5: Delivery

Processed images and descriptions get pushed back to your platform via the same integration channel they came in on. If we ingested via API, we deliver via API. If we pulled from your Shopify store, we push back to your Shopify store. The goal is that your team doesn't have to touch anything — the enhanced assets just appear where they need to be.

Why We're Cheaper Than Doing It Yourself

This is the part that surprises most people.

If you went out and tried to replicate what we do using raw API credits from image generation and language model providers, you would spend more than what we charge. Significantly more, in most cases.

Here's why.

Model Selection and Optimization

Not every image needs the most expensive model. A product photo that just needs background removal and white balance correction doesn't need the same compute as a heavily degraded image that needs full super-resolution and intelligent reconstruction.

We route each image to the most cost-effective model that can achieve the required quality threshold. Our infrastructure uses a mix of open-source models, optimized inference engines, and proprietary fine-tuned models that are purpose-built for listing enhancement. For many common operations, we're running inference at a fraction of a cent per image using distilled models that maintain 90%+ of the quality of their full-scale counterparts while cutting compute costs by 75% or more.

Off-the-shelf API pricing for image generation or enhancement typically ranges from $0.003 at the low end (basic operations with lightweight models) to $0.25+ per image for premium models at high resolution. A naive approach — running every image through a premium model — would cost you $0.10–$0.25 per image. At scale, that adds up fast: 100,000 images at $0.15 each is $15,000. A million images is $150,000.

We optimize aggressively. By batching operations, routing to the right model tier, caching common operations, and running our own inference where it makes sense, we consistently deliver the same or better quality at a fraction of those costs.

Infrastructure Efficiency

When you're processing millions of images, the infrastructure choices matter enormously. We've invested in optimized inference pipelines, smart batching, and processing orchestration that keeps GPU utilization high and cost-per-image low. This is the kind of optimization you'd need a dedicated ML engineering team to build and maintain — and we've already done it.

Volume Economics

We process images for multiple clients across multiple verticals, which gives us volume leverage with compute providers that an individual business wouldn't have. This isn't a markup game — it's a genuine efficiency advantage that we pass through to our clients.

The net result: for most engagements, our all-in cost to enhance your listing images and descriptions is lower than what you'd spend on API credits alone if you tried to build the same pipeline yourself. That's before accounting for the engineering time, the QA process, the integration work, and the ongoing maintenance.

Industry-Specific Playbooks

Different verticals have different needs. Here's how we approach each one.

E-Commerce

The typical client: A Shopify or WooCommerce store with 5,000–500,000 SKUs, inconsistent product photography from multiple suppliers, and descriptions that range from decent to nonexistent.

What we do:

• Standardize all product images to consistent white or branded backgrounds
• Upscale low-res supplier images to support zoom functionality
• Correct colors so that products look accurate on screen (reducing returns)
• Rewrite product descriptions with category-specific SEO targeting
• Generate alt text for accessibility and image SEO

Expected impact: Based on industry data, stores typically see a 20–40% improvement in conversion rates on enhanced listings, with a meaningful reduction in return rates from more accurate visual representation.

Auto Dealerships

The typical client: A dealership group with 3–15 locations, 500–5,000 vehicles in active inventory, and a mix of professional lot photos and rushed smartphone shots.

What we do:

• Normalize vehicle photos to consistent backgrounds and lighting
• Enhance interior shots (which buyers care about most) for clarity and appeal
• Ensure consistent cropping and angle presentation across all inventory
• Optimize vehicle descriptions with trim-specific details, competitive keywords, and local SEO targeting
• Process new inventory photos within hours of upload so vehicles get merchandised faster

Expected impact: Faster time-to-market for new inventory (reducing that ~$50/day cost of unmerchandised vehicles), 20–40% more VDP views, and measurably higher lead generation from enhanced listings.

Real Estate

The typical client: A brokerage or property management company with 100–10,000 active listings, photos shot by agents with varying levels of skill, and descriptions written under time pressure.

What we do:

• Enhance interior and exterior photos with improved lighting, color, and clarity
• Sky replacement on overcast exterior shots
• Straighten vertical lines and correct wide-angle distortion
• Rewrite property descriptions with neighborhood-specific SEO, accurate square footage callouts, and amenity highlighting
• Generate virtual twilight versions of exterior photos (these have been shown to increase showings by up to three times)

Expected impact: Faster sales (32% faster is the industry benchmark for professional-quality photos), higher sale prices, and more listing inquiries from search.

Hospitality and Short-Term Rentals

The typical client: A property management company running 50–1,000 short-term rental units across Airbnb, VRBO, and direct booking platforms.

What we do:

• Enhance all property photos to professional quality
• Ensure the cover image for each listing is the strongest shot (this is the single most important conversion factor on Airbnb)
• Normalize photo quality across the portfolio so all properties meet the same visual standard
• Optimize listing descriptions for platform-specific search algorithms
• Seasonal photo enhancement (e.g., adding warmth to winter shots, brightening summer images)

Expected impact: Based on Airbnb's own data, the difference between amateur and professional photography is a 2.5x multiplier in booking frequency. Even a partial improvement toward professional quality yields meaningful booking increases and supports higher nightly rates.

Restaurants and Food

The typical client: A restaurant group or ghost kitchen operating on multiple delivery platforms, with menu photos that range from professional studio shots to someone's phone camera in bad lighting.

What we do:

• Enhance food photos for color vibrancy, sharpness, and appetite appeal
• Standardize backgrounds and plating presentation across the menu
• Optimize for platform-specific image requirements (DoorDash, Uber Eats, and Grubhub all have different display formats)
• Rewrite menu descriptions with appetite-triggering language and SEO for discovery

Expected impact: Grubhub's data shows up to 70% more orders for listings with quality photos. Even conservative estimates suggest 20–30% more orders from enhanced visual presentation.

Classifieds and Marketplaces

The typical client: A marketplace platform with user-generated listing content, where photo quality varies wildly from seller to seller.

What we do:

• Automatically enhance seller-uploaded images on ingest
• Normalize backgrounds, lighting, and framing without altering the actual product
• Provide sellers with enhanced versions they can approve before publishing
• Generate or improve listing descriptions based on detected product attributes

Expected impact: Platform-wide conversion rate improvement from consistent visual quality, higher trust signals, reduced time-to-sale for sellers, and improved platform reputation.

What This Costs

We price based on volume and complexity. Here's the rough framework:

Image enhancement only: Starts at a few cents per image at scale. The exact per-image cost depends on the processing required (a simple background swap is cheaper than a full super-resolution + color correction + background replacement pipeline) and the volume you're processing.

Description enhancement only: Priced per listing. Scales down significantly at volume.

Full listing enhancement (images + descriptions): This is where most clients land. Bundled pricing is typically 30–50% less than buying each service separately.

Platform integration: We charge a flat setup fee for integrating with your existing systems, then the per-listing costs above. For standard platforms (Shopify, WooCommerce, common MLS systems, major automotive inventory tools), setup is straightforward. Custom integrations take more work but are well within scope.

For most clients processing more than 10,000 listings, our all-in cost is lower than what they'd spend on raw API credits alone to achieve the same result. We're not the cheapest option if you're processing 50 images. We're the cheapest option when you're processing 50,000 or 5,000,000.

Getting Started

The process is simple.

1. Send us a sample batch. A few hundred listing images and descriptions from your actual inventory. We'll process them for free so you can see the quality difference on your own data.
2. We'll show you the ROI math. Based on your vertical, your current conversion rates, and the volume of listings you're managing, we'll project the expected revenue impact of enhancing your full catalog.
3. Integration and rollout. Once you're convinced (and people usually are after seeing their own listings side by side), we set up the integration with your platform and begin processing. Most clients are fully live within one to two weeks.
4. Ongoing processing. New inventory photos and listings flow through the pipeline automatically. No manual intervention required. Your team keeps doing what they do; the images and descriptions just get better on the way to publication.

The Bottom Line

You're sitting on a catalog of listings that could be performing 20%, 30%, or 50% better than they are right now. The gap between where your images are and where they could be represents real revenue that you're not capturing — on every single listing, every single day.

The research is unambiguous across every vertical: better listing images and descriptions translate directly into more views, more leads, more conversions, higher prices, and faster sales. This isn't theoretical. It's measured, documented, and replicated across hundreds of studies and millions of listings.

We've built the infrastructure to close that gap at any scale, faster and cheaper than you could do it internally.

Get in touch and we'll prove it on your own data.

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