Luminar Engine is the AI vision stack behind Luminar Neo — RAW pipeline, lens correction, HDR merge, exposure, sky — packaged as a headless SDK you link into your own pipeline. No per-image fees. No cloud round-trips. Your images never leave your network.
RAW · straight off the camera
Engine output · lens + exposure + HDR
Built on the stack trusted by photographers in 141 countries · in production pilots with European market leaders processing 180,000+ images a day
# drops into the automation you already run
$ luminar-engine --in ./ingest/raw --out ./catalog/jpg \
--ops lens,exposure,hdr-merge --output-profiles 3 --cores auto
✓ 4,812 images processed · 0 left your network
If your business processes 150K–10M images a year, you already know the math:
Metered cloud APIs
Photographer-grade APIs charge up to $0.50 per photo over a fraction-of-a-cent GPU floor. At 100K images/day even mid-range metering is a seven-figure annual bill — plus upload time, lock-in, and price hikes you don't control.
Client images in someone else's cloud
61 privacy regulators issued a joint statement on AI imagery; GDPR fines over photo processing have passed €100M. "Where do our clients' photos go?" is now a procurement question. With cloud APIs, the honest answer hurts.
DIY on open source
libraw + a queue gets you basic conversion — but not professional-grade color, and someone has to maintain it and chase every new camera format. Forever.
No platform migration. No new UI for your team. The engine slots in as one automated step.
A CLI binary today, C API and Python bindings on the roadmap. Point it at an input folder, set your operations and output profiles — it fits bash-level automation without new endpoints.
RAW→JPEG · lens & perspective correction · HDR bracket merge · exposure · alignment · sky replacement. Start with one deterministic step, add packs as you grow — it doesn't need to be your entire process.
NUMA-aware scheduling pins work to your cores. When a client dumps a 30,000-image project at 6 pm, burst to every core you own. At 3 am, idle costs you nothing.
No platform migration. No new UI for your team. The engine slots in as one automated step.
| Premium cloud API ($0.05–0.22/img) | In-house build + maintenance | Luminar Engine flat license | |
|---|---|---|---|
| At 1M images per year | $50K–220K | €150–370K build + €50–155K/yr | One flat annual fee |
| At 3M images per year | $50K–220K | same + more ops | Same flat fee |
| Images leave your network | Yes | No | No |
Sources: published vendor pricing, June 2026; in-house estimate based on EU senior-engineer fully-loaded rates. Your exact quote depends on server count and operation packs.
Everything your technical lead will ask, answered in the documentation pack — before the first call if you want.
Linux x86_64 CLI binary; CPU-only baseline — runs on the EPYC/Xeon servers you already own
Offline hardware-ID activation; zero telemetry on your content
NUMA-aware core pinning for predictable throughput on multi-socket machines
Wide RAW format coverage, updated with camera releases as part of the license
Deterministic batch contract: input folder, ops list, exit codes, structured logs
Throughput benchmarks quoted per your hardware spec — not lab numbers
C API and Python bindings on the public roadmap; Docker/gRPC for fleet deployments later
1 RAW → N output profiles in a single pass
"We compared it against our manual Lightroom pipeline on a real client project. The economics weren't close — and the images never left our building, which is what our enterprise clients actually audit."
We price per server, not per image — so your unit economics improve as you grow. Exact quotes are scoped to your hardware and operation packs.
Fixed fee, credited to your first license
Flat annual · unlimited cores & volume
Custom — multi-site, embed, white-label
That's the benchmark we test against, and it's the acceptance standard we write into every pilot: your art director judges our output against your current manual process on your real projects. We publish methodology with every benchmark. Where a specific operation isn't at parity yet, we'll tell you before you sign.
The base integration is a CLI call inside automation you already run: input folder in, processed files out, exit codes and logs for your orchestration. Production teams have scoped the first working step in days. C API and Python bindings are on the roadmap for deeper integration.
Standard x86_64 Linux servers, CPU-only — no GPU purchase required. The engine bursts across all available cores and is NUMA-aware on multi-socket machines. We quote expected throughput against your exact spec as part of the pilot, not generic lab numbers.
Activation is hardware-ID based and fully offline. No cloud callbacks, no periodic license pings, no telemetry on your content. Air-gapped environments are a supported configuration, not an exception.
Format and model updates are included in the annual license — that's a core part of what you're paying for versus building in-house. Your pipeline keeps working when your photographers upgrade bodies.
At low volume, you probably should. Flat on-prem licensing wins when volume, privacy, or turnaround SLAs matter: above roughly 500K images/year the license typically pays back inside 12 months against metered pricing — and your client images never leave your network at any volume.
A 30-minute technical call: we map your pipeline, define measurable acceptance criteria, and quote throughput for your exact hardware. If the math doesn't work for your volume, we'll tell you.
Book a technical demoOr write to [email protected] — an engineer answers, not a sequence.