Every device. Every pixel.
Every context.
From one master image.

LiquiFire Resolve is an advanced web graphics workflow and optimization solution. Context-aware image optimization, virtual file naming for SEO, and rule-based content generation, delivered from a single master asset and composed through LiquiFire Chains™.

1 Master asset per product. Every device, locale, and channel derives from it.
0 Pre-rendered size ladders. Every request is resolved at render time on demand.
Outputs per chain. Format, scale, canvas, and filename are all rule-driven.
SEO Virtual filenames for category, listing, product, and localized query intent.

Image optimization alone is not a strategy.

CDN-level optimization solves a narrow technical problem. It does not address context, SEO, or the design decisions that sit behind every stakeholder visual. LiquiFire Resolve treats optimization as one step inside a wider, rule-based workflow.

Costs rise as release cycles shorten.

Creative teams are asked to ship more variants, more often, across more channels. Manual production stops scaling long before the roadmap does.

Design quality depends on finite specialists.

Consistent output across a large catalog requires either a large creative team or a system that encodes design decisions once and applies them everywhere.

Customer experience competes with back-office load.

Every front-end change that requires new images, new code, or a new template adds cost, latency, and risk to the release cycle.

Rule-based web graphics, from one master asset.

LiquiFire Resolve extends image delivery into an authoring, optimization, and SEO workflow. Chains encode the logic once; every page request triggers the right output for the device, context, and audience.

Context-Aware Optimization

The right image for the right viewport.

LiquiFire Resolve inspects the requesting device, the image container, and the pixel density, then renders a uniquely optimized variant. No pre-generated size ladders. No worst-case image weights shipped to every visitor.

  • Automatic format negotiation across WebP, AVIF, JPEG, and GIF
  • Device pixel ratio adaptation, including HiDPI and Retina displays
  • Compression balanced against the actual render target, not a preset
  • Lazy loading with Intersection Observer thresholds
Virtual File Naming

SEO filenames, dynamically assigned at render time.

Master asset names rarely match search intent. LiquiFire Resolve separates the source asset from the URL filename, so each page, category, and localized variant ships with a filename that maps to the query that would find it.

  • Category, listing, and product URLs generated from the same master
  • Localization per language or region without asset duplication
  • Metadata-driven alt text and description embedding
  • Improved crawl relevance without manual file management
Design-Led Content Generation

Rule-based canvases, countdown-driven output.

LiquiFire Chains are declarative: the design is written once and executed on every request. The same chain generates seasonal canvases, badge overlays, pricing callouts, and region-specific layouts, all evaluated at render time against live data.

  • Canvas composition with positioned overlays, text, and product crops
  • Rule and countdown-based execution for campaigns and pricing
  • User-supplied content template insertion with AI moderation
  • Front-end implementation reduced to a single URL call
Data-Driven Execution

PIM, ERP, and DAM at the render step.

The platform reads data from external systems as part of chain execution, including product data from PIM, inventory from ERP, assets from DAM, and geolocation or session data from the front end. Data is evaluated server-side and never exposed to the public.

  • JSON, XML, and HTTPS data source ingestion mid-chain
  • Conditional fallback strategy if a third-party source times out
  • GS1 barcode read and decode for 1D, 2D, QR, and Data Matrix
  • GeoIP-aware output for localized pricing, currency, and imagery

One master. Six devices. Zero pre-rendered variants.

The demo below requests the same master asset through LiquiFire Chains at six device widths. Every output is optimized for its viewport and pixel density at render time, not picked from a pre-built size ladder.

demo-resolve.html · one image, every device Live

Dynamic filenames, from a single master.

Most platforms inherit the master asset filename. LiquiFire Resolve assigns the filename at render time, which allows the same source image to be served with category, listing, product, and localized URLs, all tuned for search intent.

Category customer.liquifire.com/Sunglasses?set=…
Listing customer.liquifire.com/Ray-Ban Sunglasses?set=…
Product customer.liquifire.com/Ray-Ban Original Wayfarer Classic Black?set=…
Localized Category customer.liquifire.com/Gafas de sol?set=…
Localized Listing customer.liquifire.com/Ray-Ban Gafas de sol?set=…
One source asset ↑ All derived from the same master file

Composable, readable, and data-aware.

A LiquiFire Chain reads more like a recipe than a configuration file. Variables bind at render time, external data sources are ingested mid-chain, and the output format is decided at the last step based on the requesting device.

resolve-product-listing.chain Production sample
# Source the master asset from DAM
source=url[file:masters/(global.sku).png]
 
# Pull live inventory from ERP
jsonacquire=url[https://erp.internal/stock?sku=(global.sku)],name[stock]
 
# Overlay a stock badge if inventory is low
annotate=font[DMSans-Bold],pointsize[28],fill[#b45309],
        gravity[northeast],text[Only (global.stock.qty) left],
        if[(global.stock.qty < 10)]
 
# Scale to the requesting container
scale=width[(resolve.width)],height[(resolve.height)],fit[container]
 
# Let the browser negotiate format
sink=format[(resolve.format)],quality[(resolve.quality)],expires[+1 day]

Chain edits take effect on the next request. No CMS template updates. No front-end redeploy. The chain is the contract between creative decisions and the live page.

Beyond CDN-level optimization.

Generic image optimizers focus on bytes over the wire. LiquiFire Resolve treats optimization as one step inside a composable graphics workflow, with rules, data, and SEO built in.

Capability LiquiFire Resolve Typical image optimizer
Image optimization and format negotiationIncludedIncluded
Context-aware optimization per device and containerIncludedNot offered
Rule-based execution inside a chainIncludedNot offered
Virtual file naming for SEOIncludedLimited or not offered
Unlimited commands without SDK-imposed URL length limitsIncludedRestricted by URL length
Design-led canvas and content generationIncludedNot offered
PIM, ERP, and DAM data source executionIncludedNot offered
AI auto-upscale, auto-crop, and alt descriptionIncludedPartial, varies by vendor
GeoIP-based localization mid-chainIncludedNot offered
Advanced HTTP cache control at the originIncludedLimited

LiquiFire Resolve integrates with an existing CDN and extends cache control at the origin, so the platform complements current infrastructure rather than replacing it.

Integrate with your stack, not around it.

LiquiFire Resolve is part of LiquiFire OS and deploys wherever the platform deploys. Assets stay where they are; the chain runs adjacent to the systems that already own the data.

CDN-friendly

Works alongside the existing CDN.

Resolve extends cache control at the origin so outputs can be purged or versioned without clearing the entire edge cache.

Assets in place

No forced migration.

LiquiFire Resolve reads masters from DAM, S3, or a local file path. There is no parallel asset library to maintain.

Minimal footprint

Small front-end surface.

A single JavaScript library and a set of data-resolve attributes on image tags. No heavy SDK. No per-request URL-building on the client.

LiquiFire OS

Every deployment model.

SaaS, on-premises appliance, air-gapped, and hybrid. Rule-based workflows run the same way across every deployment model.

Put LiquiFire Resolve to work.

If image optimization is already on the roadmap, LiquiFire Resolve is the version of that project that also covers SEO, rule-based canvases, and data-driven output. We will walk through the integration path and scope the change against the existing stack.