Let's Enhance vs neural.love

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan: Both have one
Public API: Both have one
Best fit: Let's Enhance: Enlarging product or portfolio shots for large-format print · neural.love: Restoring, upscaling and colorizing archival photos and footage
Trust score: About even — Let's Enhance 92, neural.love 90
Status: Both up at our last check (Oct 16, 2026)

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

Let's EnhanceUpscales, sharpens and restores photos for print-grade output

neural.lovePhoto and video restoration plus generation on shared credits

Side by side

Fact	Let's Enhance	neural.love
Category	Image Upscaling & Restoration	Image Upscaling & Restoration
Pricing model	Freemium	Freemium
Starts at	$12/mo	—
Public API	Yes	Yes
Trust score	92 / 100	90 / 100
Platforms	Web, API	Web, API
Company	LetsEnhance, Inc.	Neural Love OÜ
Launched	2017	2020
Last verified	Oct 16, 2026	Oct 16, 2026

What our research says

Let's Enhance

The safe browser-based choice when you need resolution for print and do not want to install Topaz or babysit a local upscaler; it is priced per image, so it punishes high-volume use.

Pros

Credit rollover up to six months' worth is more forgiving than the usual use-it-or-lose-it model
Distinct tools per job (sharpen, restore, unblur, upscale) instead of one catch-all slider
Documented API with separate enhancer and upscaler endpoints for production use
Running since 2017, so the model quality has had many iterations behind it

Cons

Free tier is 10 signup credits and stamps a watermark on output
One credit per image makes bulk catalogue work costly next to a one-off desktop licence
Top personal plan is 500 credits at $45/month, which is a low ceiling for agencies
Newer generative upscalers produce more dramatic detail on heavily degraded sources

neural.love

Come here for restoration and upscaling of old material rather than for generation, which is where this team has been strong since its archival film work. For new image creation, Krea or Magnific will give you noticeably better output per credit spent.

Pros

Upscaling and colorization are the original specialty and still the strongest part
Single credit balance spans subscription allowance and one-off top-ups
Public API with reference documentation for automated pipelines
Free public-domain image library alongside the paid tools

Cons

Prices and credit rates are not readable without loading the app, which makes budgeting awkward
Generation quality sits behind current image-model front-runners
Credits are spent per job, so unsatisfying runs still cost you
Small team relative to competitors, so feature pace is uneven

Which one fits

Choose Let's Enhance if you need

Enlarging product or portfolio shots for large-format print
Restoring scanned or damaged family photos without desktop software
Teams wiring upscaling into a pipeline through the API instead of a UI

Choose neural.love if you need

Restoring, upscaling and colorizing archival photos and footage
Cleaning up low-resolution assets before print or video use
Batch enhancement automated through the API
Users who want one credit pool spanning several media tasks