StacklineIQ
An enterprise registry that maps the best-in-category AI tool to every business function and product-lifecycle stage, with sourced pricing kept current in version control — not another listicle.
The Problem
Every business function now has a dozen plausible AI tools, and picking one usually means half a day of open tabs — vendor pricing pages, “best AI tools for X” roundups that are stale or sponsored, and no way to see how a choice for Sales connects to what Support or Product already run. An enterprise buyer needs one place to answer “what’s the best tool for this job, at this stage, and what does it actually cost” — with a source attached, not a guess.
What it does
Maps 14 business functions across the 7 stages of the product lifecycle, with roughly 57 tools researched directly from vendor pricing pages — no invented numbers, and no price shown for a vendor who doesn’t publish one. A function × phase matrix and a searchable, filterable registry get you to a shortlist fast. A Stack Builder turns a team size and budget into a recommended set of tools with a cost estimate. An interactive architecture canvas shows how functions hand off to each other, and a per-function adoption roadmap (Pilot → Scale → Optimize) turns a tool pick into an actual rollout plan instead of a purchase decision made in isolation.
How it is built
Fully static — every route is prerendered at build time, so there’s no server to run or secure. Tool, function and lifecycle-phase data lives in typed, Zod-validated JSON rather than in application code, so adding a tool or correcting a price is a small, reviewable diff. A validation script runs automatically before every build and fails it on a schema violation, a reference to an unknown function or phase, or a tool whose badge contradicts its own pricing model — a bad data change can’t reach a deploy.
A simple tech stack workflow to understand
Tool / function / phase data (Zod-validated JSON)
→ npm run validate:data (schema + cross-reference checks, runs pre-build)
→ Next.js static build (every route prerendered)
→ registry, matrix, Stack Builder and architecture canvas all read the same data
→ Vercel (static hosting)Nothing in the app calls an LLM at runtime — the AI tooling is the subject of the registry, not something the registry itself runs.
Where it stands
Live on Vercel; source on GitHub.