ApyGuard VS ViewForge

ApyGuard's answer

ApyGuard starts from source code, not traffic. Most API security platforms watch production traffic to discover APIs — which means they can only see endpoints that are already deployed and receiving requests. ApyGuard discovers endpoints directly from the codebase, generates OpenAPI documentation from what it finds, and tests for OWASP API Top 10 issues — especially authorization flaws like BOLA and BFLA — before the code ships. It also comes with APIScout, a free VS Code extension (also on Open VSX for Cursor and Windsurf) that runs endpoint discovery entirely locally, so no code ever leaves the developer's machine. And unlike most of the category, pricing is public and self-serve, starting at $129/month.

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.

ApyGuard's answer

It depends on your situation, honestly. If you're an enterprise with a security operations team and a six-figure budget, traffic-based platforms are mature options. ApyGuard is built for the teams those platforms don't serve: startups and SMBs that ship APIs every week without a dedicated AppSec department. Compared to spec-first tools, ApyGuard doesn't require you to already have an OpenAPI file — it generates one from your code. Compared to traffic-based tools, it tests pre-production instead of after exposure. Compared to per-endpoint enterprise pricing, it starts at $129/month with a seven-day trial, no credit card and no sales call. You can find out what your API actually exposes the same day you sign up.

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.

ApyGuard's answer

Backend developers, DevSecOps engineers, and engineering leaders at startups and small-to-mid-sized technology companies — typically SaaS, fintech, e-commerce, and healthcare teams. A fast-growing part of our audience is teams building with AI assistants like Copilot, Cursor, and Claude Code, who need to know exactly which endpoints their AI-assisted codebase actually exposes.

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.

ApyGuard's answer

The recurring problem: teams almost never had an accurate picture of the APIs their applications exposed. OpenAPI files went stale, undocumented endpoints shipped every sprint, and the tools that could help were priced and designed for large enterprises. AI coding assistants made the gap worse - code ships faster than anyone documents or reviews it. ApyGuard was built to close that gap from the source code side: discover what's really there, document it automatically, and test it before production - at a price a startup can actually pay.

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.

ApyGuard's answer

Python (static analysis and scanning engine) TypeScript (web application and VS Code extension)

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