From the Founder Last updated August 2026 · 8 min read

Why We Built Clad9 After Hadaa

Hadaa started with a messy backyard and a simple, stubborn belief: professional-grade design shouldn't require a five-figure budget or weeks on a waitlist. Two years and 180+ countries later, the same belief pointed somewhere unexpected — not at another outdoor space, but at the closet a few feet from where most of us start every single day.

FK

Francis Karuri

Founder & CTO, Hadaa · Founder, Clad9

The Story Behind Clad9: An AI Stylist for Your Closet

The Same Problem, a Different Room

Hadaa's origin story is on our About page, but the short version: designing an outdoor space was broken two ways. It was expensive — a landscape architect could mean thousands of dollars and weeks of waiting for one static plan. And it was painful for everyone else — decades-old professional software, or “AI” tools that smeared a filter over a photo and understood nothing about the actual space. We wanted to fuse the creative freedom of generative AI with the discipline of real design, so a homeowner with a phone photo could get what used to take a professional and a five-figure budget.

Somewhere around the 200,000th render, a pattern became impossible to ignore. A yard is an asset a person already owns, sitting there mostly unplanned-around because planning it properly was always expensive or slow. A closet is exactly the same shape of problem, just indoors. Most of us own more clothes than we think we do and still stand in front of them most mornings with nothing to wear — not because the clothes are wrong, but because there was never an affordable, instant way to actually plan around what's already there.

The industry figure often cited is that people wear roughly 20% of their wardrobe 80% of the time. Whether that exact split holds for any one person or not, the shape of it is instantly recognizable: a closet that looks full from the doorway and still feels empty at 7am, because most of what's in it is effectively invisible to the morning decision. That's not a shopping problem. It's a visibility problem — the same underlying failure as a yard nobody's gotten around to planning, just measured in outfits instead of overgrown beds.

Once you've built the fix for one version of that problem — and watched it actually work, at scale, for real people — the second version stops looking like a new industry to break into. It starts looking like the same engineering problem, wearing a different room's clothes.

What Building Hadaa Taught Us

Before Hadaa, I spent years building automation and AI systems at production scale — document-extraction engines reaching 98%+ accuracy, recommendation systems on vector search and semantic indexing, ML systems running inside HIPAA-compliant healthcare infrastructure. None of that was landscaping-specific. It was pattern-matching, structured extraction from unstructured input, and building recommendation logic people could actually trust — the same three problems Clad9 needed solved, just aimed at a closet instead of a yard or a patient record.

Structured extraction from a messy photo

Hadaa's Sketch Engine doesn't paint a texture over a napkin drawing β€” it reads the lines as spatial data first: boundaries, paths, beds, structures. Clad9's wardrobe capture is built on that same discipline, pointed at a video instead of a sketch: identify each garment as it passes the camera, strip the background, and extract its category, color, pattern, fabric, and fit automatically, rather than treating the footage as one flat clip to eyeball.

A verification layer under every suggestion

Hadaa's Biological Engine won't put a tropical palm in a Minnesota render β€” every plant gets cross-checked against real hardiness-zone, rainfall, and sun-exposure data before it's allowed into a design. Clad9's plan runs the same instinct on color and body: a recommendation only ships once it's been checked against what actually suits the person wearing it β€” their undertone, their proportions β€” not just whatever looks nice floating in isolation on a mood board.

Automation that removes the manual step entirely

Garden Autopilot turns one yard photo into 22 finished renders from two clicks, not a dozen rounds of manual iteration in design software. Clad9's wardrobe capture is built on the identical premise: a single video instead of photographing every item one at a time, which is the single biggest reason people download a closet app and quietly abandon it within a week.

Context the recommendation is actually built around

Hadaa designs for a real hardiness zone β€” a Zone 5b Chicago yard draws from an entirely different plant palette than a Zone 10a Phoenix one, not a generic template that ignores where the yard actually sits. Clad9's calendar-aware dressing is built to apply that same logic to time instead of geography: it designs for your real Tuesday β€” the 9am pitch, the flight, the first date β€” not just β€œTuesday’s weather.” A recommendation is only as good as the specific context it's actually built from.

The Same Philosophy, Applied to Getting Dressed

Hadaa's philosophy has always been that great design shouldn't be a luxury — professional tools that put control in your hands, instant feedback, no gatekeepers, no waiting weeks for one static answer. Clad9 is that same sentence with “design” swapped for “style.” A personal stylist, a color consultant, and a wardrobe strategist are all genuinely useful — and genuinely priced and scheduled like the luxury services they've always been. Clad9's bet is that the same automation-first approach that took landscape design from $3,000-and-three-weeks to a couple of minutes can do the same thing for the outfit you put on tomorrow morning.

That's also why Clad9 didn't launch by asking people to pay first. The color-pairing and outfit-combination logic — the same real color-theory engine the rest of Clad9 is built around — is live and free at clad9.com/colors and clad9.com/style today, no account required. Prove the logic works before asking anyone to trust it with their closet.

There's a second, quieter piece of the philosophy too: two very different ways of wanting help. Some mornings — with a yard or a wardrobe — you want a decisive answer and nothing else: just tell me what to plant, just tell me what to wear. Other days you want to stay in the driver's seat, testing ideas with fast feedback instead of being handed one verdict. Hadaa built both into Pro Studio and Autopilot side by side rather than picking a lane. Clad9 is built the same way — a decisive daily outfit when you want one, and a creative canvas with live color-and-fit feedback when you'd rather build the look yourself.

Getting It Right the Second Time

Building a second product after a first one that actually worked changes how you build it. With Hadaa, we obsessed over every detail, put an early version in front of a handful of people, and the honest signal was simple: they didn't want to give it back. That's the bar Clad9 gets held to as well — not “does the demo look impressive,” but “does a real person keep coming back to it on an ordinary Tuesday morning.”

The specific lesson that traveled straight over is about the first five minutes. Hadaa's biggest unlock wasn't a smarter render — it was removing the step where a homeowner had to learn design software before getting any value at all. One photo, two clicks, a finished result. Clad9's entire wardrobe-capture design starts from the same insight: the reason people quit closet apps isn't that the recommendations are bad, it's that nobody finishes onboarding. A single video instead of photographing forty individual items is the styling-app equivalent of “upload one photo instead of learning SketchUp.”

The other lesson is about trust, and it's why this article exists in the form it does. Hadaa earned trust by being specific in public — real botanical names, real hardiness zones, real bill-of-quantities numbers instead of vague AI-generated confidence. Clad9 is held to the same standard: its own site marks exactly which features are live and which are still shipping, in plain language, rather than blurring the two to look further along than it is. A styling recommendation you can't trust is worse than no recommendation at all — the same reasoning that put a verification layer under every plant Hadaa suggests.

Where Clad9 Actually Is Today

Hadaa took two years and seven engines to get where it is now. Clad9 is on its own version of that path — shipping milestone by milestone rather than all at once, and saying so plainly rather than implying the whole vision already works. Signing up opens a 14-day free trial, no credit card required, and the two tools above stay free regardless.

For the full, always-current rundown of every feature — wardrobe capture, body-and-color analysis, calendar-aware dressing, virtual try-on, and the rest of the roadmap — we wrote the complete breakdown here: Clad9: The AI Wardrobe App With a Stylist Built In.

Frequently Asked Questions

Is Clad9 part of Hadaa?
Clad9 is a separate product from the same team behind Hadaa's AI landscape design engine, applying the same automation-first approach to personal styling instead of yards.
Who built Clad9?
Francis Karuri, Hadaa's Founder & CTO, and the same team that built Hadaa's photo-to-render landscape pipeline.
Why did Hadaa's team build a wardrobe app?
Building Hadaa surfaced a pattern well beyond landscaping: people own real assets β€” a yard, a closet β€” but lack an affordable, instant way to plan around them. Clad9 applies that fix to getting dressed.
Is Clad9 free to try?
The color-pairing and outfit-combination tools are free forever, no signup, at clad9.com/colors and clad9.com/style. A full membership starts with a 14-day free trial, no credit card required.

Your closet, understood

Clad9 — 14 days free.
No credit card required.

Scan your closet with one video, get outfits matched to your body, your colors, and your day. Or start free right now with the color-pairing and outfit-combination tools — no signup at all.