getAIwork VS ViewForge

getAIwork's answer

The published articles run on WordPress.

The Work Board and the pipeline behind it are custom built. Listings are ingested from multiple job sources several times a day, passed through an automated screening and de-duplication pass, then queued for human approval before anything appears publicly. Filled and expired roles are removed on the same daily cycle.

Aggregate statistics are generated from that pipeline and published as static JSON at getaiwork.com/stats.json under an open attribution licence, alongside a human-readable version at getaiwork.com/stats.

ViewForge's answer:

• TypeScript
• Shopify metaobjects, as the fitment data store
• Shopify theme app extensions for the storefront components: fitment search, saved-vehicle garage, compatibility table, product-page fit notice
• Shopify Storefront API, for querying fitment from the theme
• Shopify Admin GraphQL API, for writing and exporting fitment records
• NHTSA vehicle database, for VIN decoding
• ACES and PIES XML parsing, for automotive catalog import

getAIwork's answer

It started from screening job postings in bulk and noticing how much of what circulates about AI work is either out of date or simply invented. Boards were full of roles that had closed weeks earlier, and articles quoted earnings figures nobody could source.

The response was to build the boring version. Screen everything, have a human approve what goes live, delete listings the day they are filled, quote pay only as the posting states it, and publish the underlying counts openly so anyone can check them.

The training and certification grew out of the same work. Screening tens of thousands of postings shows you fairly clearly what employers actually ask for, which turns out to be a better curriculum than guessing.

ViewForge's answer:

ViewForge came out of agency work. Normal View was building for a parts retailer running roughly 12,000 SKUs who needed fitment search, and every app we evaluated stored the merchant's compatibility data in the vendor's own database.

That is a strange trade when you look at it directly. Fitment data is genuinely expensive to produce — it is weeks of work — and the merchant would not own the result. It would belong to whichever app happened to be installed that year.

Shopify metaobjects made a different answer possible: write fitment as native structured data inside the merchant's own store. The theme reads it, the Storefront API queries it, Admin GraphQL exports it, and it is still there after an uninstall. That decision is what the rest of the app is built around.

Everything else came from real catalogs rather than a roadmap. Eight verticals exist because a tractor catalog is not Year/Make/Model. Smart Parse exists because that retailer had already written fitment into 12,000 product titles, and nobody was ever going to retype them.

getAIwork's answer

Only if the screening is what you care about. If you want maximum volume, a large aggregator will always list more roles. getAIwork deliberately lists fewer, because a person removes the ones that are filled, duplicated or not genuine.

The Work Board is also free and public, with no signup and nothing to buy. That is unusual in this category, where screening is normally the thing kept behind the paywall. The paid membership is the training and the human-graded certification, not access to the listings.

And pay is shown exactly as each posting states it, never estimated or modelled. There are no income claims anywhere on the site, which rules getAIwork out for anyone looking to be told what they will earn.

ViewForge's answer:

Data ownership. Fitment lives in your Shopify metaobjects, so uninstalling does not take your compatibility data with it. Convermax, EasySearch and PartFinder all keep it in their own databases, and getting it back depends on their export tooling on the day you cancel.

Cost at the low end. The search widget, the compatibility table on the product page and the saved-vehicle garage are all on the free tier, up to 50 products, with no expiry. EasySearch puts the table and the garage behind its $75/month Premium plan. Convermax starts at $250/month.

Automotive and non-automotive coverage. Eight built-in templates, and fully custom templates from $19/month, for catalogs that do not decompose into Year/Make/Model at all.

getAIwork's answer

Two things, both fairly unglamorous.

First, every listing on the Work Board is approved by a person before it goes live, and listings are deleted the day the role is filled rather than left to decay. Most boards in this space aggregate automatically and let expired postings pile up, which is the standing complaint readers have about nearly all of them. Removing listings is the unglamorous, permanent job that makes the board worth trusting.

Second, the underlying market data is published openly instead of being kept as a marketing asset. 39,389 postings screened to date, roughly 1,363 live at any one time, and listed pay aggregated into percentile bands by field. It is published at getaiwork.com/stats and as machine-readable JSON at getaiwork.com/stats.json, free to reuse with attribution, so everything claimed above is checkable rather than asserted.

ViewForge's answer:

Three things. (1) Data ownership: ViewForge writes fitment as Shopify metaobjects native to your store — most competitors store fitment in their own database. (2) 8 verticals out of the box: auto, motorcycle, tractor, marine, power equipment, bicycle, printer, electronics — most competitors are automotive-only. (3) Smart Parse: extract fitment automatically from your existing product titles and descriptions instead of re-typing everything.

getAIwork's answer

People trying to get into AI work, rather than people already established in it. Roughly three groups.

Career changers with no AI background looking for a realistic entry point. Freelancers and contractors adding AI work to what they already do. And people looking specifically for recurring paid platform programmes, meaning annotation, evaluation and model-training work, which is now close to half of everything open on the board.

The audience is global rather than US-centric, and a meaningful share are non-coders: writing-centred work is about 27% of currently open listings, against 68% technical.

On remote, the honest figure is that 564 of 1,351 currently open listings are tagged remote, about 42%. That share has drifted down slightly since late August rather than up, so this is not the remote-only market it is often described as.

ViewForge's answer:

Shopify merchants whose customers need to know whether a part fits before they will buy it — and who do not have an engineer on staff to build that themselves.

Concretely: auto and truck parts retailers, powersports and motorcycle dealers, tractor and agricultural parts sellers, marine and outboard suppliers, small-engine and power equipment stores, bicycle and e-bike component shops, printer supply merchants, and electronics accessory sellers.

Catalog sizes run from a few dozen products on the free tier up into the tens of thousands; it is running in production on a catalog of roughly 40,000 SKUs. The common thread is not the industry — it is that "does this fit my thing" is the question deciding the sale.