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Discover and compare developer tools, get curated stack recommendations, and build visual tech stack diagrams - tech stack builder & tools directory platform for developers and founders.

Year/Make/Model fitment search for Shopify. 8 verticals, Smart Parse, and your data in Shopify metaobjects — not a vendor database. Free tier, Pro at $49.
Website, pricing, platforms and company facts side by side.
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| Website | tekyous.dev | normalview.pro |
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| Company | Startup from Poland · 1 - 9 employees · 2026 | Startup from the United States · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


Tekyous is an interactive tech stack builder and tools directory platform that helps to visualize, compare, and optimize tech stacks in one place. You pick a tool on the canvas, and in real-time you get suggestions on what you can add next, how your tools pair together, or what can be missing....
ViewForge is a Year Make Model (YMM) parts finder for Shopify. Shoppers pick their vehicle, machine or device from cascading dropdowns and see only the parts that fit. Fitment search works across eight verticals — auto, motorcycle, tractor, marine, power equipment, bicycle, printer and...
What each product offers, as listed by its team.


An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of ViewForge yet.
Walkthroughs and reviews on video.
Tekyous - Interactive Tech Stack Builder | Platform Demo
ViewForge: YMM Search & Filter
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Tekyous.dev and ViewForge.
Tekyous.dev's answer
ViewForge's answer:
Tekyous.dev's answer
Tekyous combines two things that have always been separate:
Tekyous adds third layer - contextual - by putting the tools on the canvas and offering real-time recommendations.
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.
Tekyous.dev's answer
To combine the informational, visual and contextual layers in one place.
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.
Tekyous.dev's answer
Primarily developers and founders who need to make tool decisions. That includes:
But tekyous is not limited to a purely technical audience. The catalogue includes AI and no-code tools alongside traditional developer tooling — making it a useful starting point for non-technical founders who want to understand the modern technology landscape. The interactivity of the platform, paired with the learning resources linked to each tool, can make the tech world feel more approachable.
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.
Tekyous.dev's answer
No matter if it's web application, automation or data pipeline, exactly the same results can be achieved with many different tools. And this abundance of options for building projects can be staggering and intimidating at the same time , leading to not always the best choice of tools, or a fear of missing out by not following new releases every week.
And that was the reason to build Tekyous - a single place to discover and compare developer tooling without the noise, and to visually plan a stack before committing to it.
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.
Share your experience with using Tekyous.dev and ViewForge. For example, how are they different and which one is better?
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