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Noteworthy Investors

Executives from the biggest beauty brands are investing in us.

Our Potential Looks as Good as Our Lashes

3X
More Appointments
$20B
Global Market
INVEST IN LUUM

On The Front Lines Of Innovation

Repetitive, precise, and physically demanding tasks in the beauty industry are perfect for technological disruption. By bringing our robotics and AI to this multi-billion dollar market, LUUM will stand at the forefront of innovation.

20-40%

of American women have already tried eyelash extensions

34K

US businesses were offering eyelash services pre-pandemic

30%

annual lash extension market growth pre-pandemic

$1,200

is spent each year on eyelash extensions and monthly refills for the average consumer

Demand

for eyelash extensions is on track to surpass Botox

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Created To Scale Business Margins

Our automation robotics are designed to improve business margins with higher quality and safer lash extension services in just 25 minutes.

3X More Clients Per Day
100% Safe
200% Faster Appointments
Collaborates With Artist
Compact Size
Consistent, Quality Results

How LUUM Works

1
The eyelash extension robot integrates into existing space to work alongside lash artists for enhanced results.
2
The robot computer vision “sees” the unique client and adjusts in real-time, pausing when it detects motion and resuming when the client is still.
3
Feather-light plastic wands, which fall away in the unlikely event of contact with anything other than the lash, precisely isolate each eyelash to adhere extensions.
4
The AI platform leverages machine learning by improving performance with each service.
5
Lash artists can now redirect energy from painstaking manual installation to artistry, stylization, and customer satisfaction.
1
Collaborative eyelash extension robot integrates into existing space to work alongside lash artists for enhanced results.
2
The robot computer vision “sees” the unique client and adjusts in real-time, pausing when it detects motion and resuming when the client is still.
3
Feather-light plastic wands, which fall away in the unlikely event of contact with anything other than the lash, precisely isolate each eyelash to adhere extensions.
4
The AI platform leverages machine learning by improving performance with each service.
5
Lash artists can now redirect energy from painstaking manual installation to artistry, stylization, and customer satisfaction.
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Our Expansion Strategy

We will utilize the funds from investments to optimize our technology for faster and even higher quality output. We also plan to expand into additional high-volume market verticals, including leading beauty retailers, medi-spa chains, lash-service providers, luxury hotel chains, and even high-end hospitality destinations.

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A Business Model Setup For Success

$125,000 robot generates $3 million in revenue. 30% goes directly to LUUM within only 6.5 months.

We plan to expand to more market verticals like leading beauty retailers, medi-spa chains, luxury hotel chains, and more.

Branded Luum Salons

As a secondary plan of action, we will own and operate our own LUUM salons and bring our advanced technology platforms to brand new locations.

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The World’s First Eyelash Extension Robot

LUUM is on track to be the first company to take robotics to the projected $20 billion global eyelash extension market, making us a true category creator.

Robust patent portfolio that makes it difficult for competitors to emerge

Lashes are non–medical, eliminating the need for FDA approval or MD supervision

Our patented technology platform is the first of its kind in the industry

Board of ophthalmologists & dermatologists to ensure highest safety standards

Deal Terms

Offering Circular

$1.10

Price per Share

$990

Min. Investment

45,445

Shares Offered

Reg CF

Offering

$50,000.50

Offering Min

Nonvoting Common Stock

Offering Type

The LUUM Crew

INVEST IN LUUM LASH TECHNOLOGY

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Business Updates

Nathan Harding’s Post

LUUM awarded 3rd Korean patent!“Method and Device for Evaluation of Eyelashes”At LUUM, we apply eyelash extensions with groundbreaking robots (Become a shareholder at invest.luumlash.com). Depending on your background, you may know South Korea as having one of the hottest robotics communities, or you may know South Korea as the birthplace of eyelash extensions, but since it happens to be both, we always take special pride in seeing our patent applications accepted there. This application patents how you find isolated natural eyelashes on a client before extending them. It broadly patents any machine that uses a robot to probe the lashes and a computer vision system to measure them. This protects us in the case that someone tries to build a machine to do even half the job i.e. just isolate the natural lashes and let a human apply the extensions. Building such a machine would not be a bad idea, because isolating lashes can be the hardest part of the procedure. Of course, another patent we’ve been awarded in Korea covers a machine that would extend them as well. We want to cover all the possible ways other companies might want to compete with us, because when our machines are in stores demonstrating their astounding profitability, they are going to wish they could enter the market!

Oh no!
Our engineers sabotaged our computer-vision!

OK, full disclosure, it was on purpose and we do it to all the time for testing. It looks really cool, though, and is a nice demonstration of the real-time reactivity that’s required in a system like this (because we’re working on humans and they move and fidget sometimes!).

The video below shows our engineer basically poking a (teeny tiny) stick into the cameras’ field of vision as the system assesses whether an individual natural lash is ready to have an extension applied.

Context: The first task our system needs to complete when preparing to apply a lash extension to a human lash, is to isolate a “target” lash from the lashes around it (this ensures we don’t glue an extension to multiple lashes at once, the cardinal sin in lash extensions). The system also can’t just place an extension just anywhere along the client’s lash — it has to place it within a millimeter (or so) of the client’s eyelid (without touching it). This ensures the lashes look natural and stay put (and we don’t get extension lashes dangling from the end of clients’ eyelashes).

The target lash is red 🔴. The lid-line is outlined in yellow 🟡 (by a neural network!).

When the system sees that the millimeter of lash-space closest to the lid-line is free of obstacle (isolated), it bounds it in a cyan box — good to place a lash!

When the engineer pokes the little “stick” into that space, the system sees that it's no longer isolated enough for an extension and turns the box magenta — no-go for a placement.

These assessments happen thousands of times through the course of a client appointment!

Note - all stick-poking is done under very safe and controlled conditions and should not be tried at home.

Isolation Targeting Neural Network Win at LUUM

Another Machine Learning Win at LUUM!

At LUUM we install eyelash extensions with robots, and I’ve shared before that a key part of our machine vision strategy at LUUM has been to get to market quickly using traditional computer vision techniques, and then build data to train neural networks which will improve the performance in the long run. As the neural networks become smarter, they are slowly replacing our older code.

 

Before you place an eyelash extension, you need to isolate a “target lash.” That means that you need to separate it from other eyelashes around it.. The first part of this video shows the basic process of isolation: One of the isolation prongs moves up out of the lashes, then plunges back into the lashes, and then makes a spreading motion. The only hard part of this process (for a robot!) occurs after it moves up out of the lashes: How does it decide where to plunge back into the lashes? The target it picks will determine whether it isolates a lash or not. 

Using data from thousands of attempts to isolate lashes, we’ve been training various neural networks to make this decision. The second part of this video shows a comparison of two different test runs on our “difficult-isolation-test-bed.” (The difficult-isolation-test-bed is a mannequin head fitted with synthetic lashes that are much harder than normal to isolate.) The video only shows still images of the lashes right after an isolation attempt. If you see an isolated lash with a cyan colored box around it, that’s paydirt. That means it properly isolated a lash. The test run shown on the left is using our latest neural network, the test run on the right is our older software which uses traditional computer vision and heuristics. You can see that the test run using the neural network is getting many more isolations. That’s the power of machine learning!

 

Congrats to our Director of Machine Learning Prasad P. Nair, Ph.D. and our team at DeepEdge for another AI win!

Extension Present Neural Network Win at LUUM

One More Neural Network Win at LUUM!

At LUUM we install eyelash extensions with robots, and I’ve shared before that a key part of our machine vision strategy at LUUM has been to get to market quickly using traditional computer vision techniques, and then build data to train neural networks which will improve the performance in the long run. As the neural networks become smarter, they are slowly replacing our older code.

 

The video comes from one of the cameras on our placement robot. Its job is to pick up and place extensions. It is holding a three stranded “3D volume” lash extension in its end effector. When it picks up an extension, the first thing it needs to do is determine whether it successfully grabbed it or not. Once we know that an extension is present, we need to inspect it and determine a lot of things, but we don’t want to waste any time doing that if the extension simply isn’t there. Enter machine learning: we’ve trained a neural network to determine whether extension presence is true or not-true. It does this extremely quickly: 5 milliseconds. That is one of the great things about NNs - they’re really fast! The video shows the output traces of many other computer vision tasks which are performed by traditional techniques and other neural networks. None of those traces would be calculated if the new neural network hadn’t given the OK first - saving valuable time. The case shown here is an easy example, but in fact the neural network also works very well when the background is confusing. This is the fourth of many neural networks we will deploy over the next two years.

 

Congrats to our Director of Machine Learning Prasad P. Nair, Ph.D. and our team at DeepEdge for another AI win!

New Patent: WINK005IL Allowed (First Patent in Israel)

“Detachable End Effectors for Cosmetics Robotics”

Israel gave us the first allowance on this invention, which relates to the breakaway end effectors used by the robot during the lash application process. An important aspect of the invention is the use of magnets to hold the end effectors to the hard robotics - magnets are an underappreciated passive mechanism that have become much more effective since the widespread availability of rare earth magnets. They’re ideal for this application since the force is highest when they’re in contact (so small forces won’t disturb the end effector) and the force drops off quickly as a gap opens up (so the end effector won’t reengage if a large force does disturb it).

new Patent: WINK002US Allowed (Third U.S. Patent)

“Eyelid Covering and Stabilization For Automatic Eyelash Extension”

When we started working on robotically applied eyelash extensions there were no patents for any such thing, and very few patents related to eyelashes at all. But of the handful out there some do relate to eye masks - after all, the manual process of eyelash extension involves placing tape to cover the lower lashes and sometimes tape on the upper as well. So we had to tread carefully to avoid the well traveled aspects of eyelash extension eye masks for manual application. Fortunately we had already reimagined much of the process in order to automate it, and the eyemasks we use with the lash applicator are quite a bit different from those used in manual eyelash extension. The US patent office recognized that when they granted us this patent, our third in the US, earlier this year. But, here is the funny thing: the design is so novel, they allowed us to patent combination upper/lower eyemasks for the manual process as well!

Ulta Press Release - Business Wire

Ulta Beauty invests in LUUM! And you can too!

We’re excited to announce we just closed a round of funding with amazing institutional and strategic investors, including #1 US beauty retailer, Ulta Beauty! *

Even better news - we’ve launched our next crowdfunding campaign, so anyone can get in on the ground floor alongside Ulta and the rest of our fabulous institutional backers!

We Were Featured in Beauty Independent!

Thrilled to be featured by Beauty Independent about closing our last round with amazing investors, including Ulta Beauty! "Cutting-edge technology has a place in beauty to make consumers' experiences better and drive profitability for service providers," says our CMO Rachel Gold.

3rd Neural Network Deployed to Break Robot Mask Addiction

At LUUM we do eyelash extensions with robots. For years LUUM’s clients have always worn a COVID mask. What started out as a public health precaution turned into a necessity for the vision system – it turned out that the white masks made a great background for the machine vision and made it simple to identify the black tip of our extension handling end effector (We usually call it “the wand.”). But it’s not something we want to do forever (who does!?) and the classic edge-finding computer vision techniques we were using to find the tip of the wand still weren’t that robust. Even when the client is masked, it’s always possible to get shadowing around the mask and lose contrast at the edge of the wand tip. Then the system has to back out and try again.  That’s where our third machine learning win came in – a Neural Network designed in conjunction with our partner DeepEdge now recognizes the tip even without a mask.  In this video, our system is running a test cycle (one where it doesn’t let go of the extension after placement); if you watch carefully as the extension sails into place, you’ll see the dummy is completely without a mask. If we’d posted the same video last year, the dummy would’ve had a mask on because we couldn’t successfully place it without them.

FAQs

Why invest in startups?
Crowdfunding allows investors to support startups and early-growth companies that they are passionate about. This is different from helping a company raise money on Kickstarter. With Regulation CF Offerings, you aren’t buying products or merchandise. You are buying a piece of a company and helping it grow.
How much can I invest?
Investors other than accredited investors are limited in the amounts they are allowed to invest in all Regulation Crowdfunding offerings (on this site and elsewhere) over the course of a 12-month period: If either of an investor’s annual income or net worth is less than $107,000, then the investor’s investment limit is $2,200, or 5 percent of the greater of the investor’s annual income or net worth, whichever is greater. If both an investor’s annual income and net worth are $107,000 or higher, then the investor’s limit is 10 percent of the greater of their annual income or net worth, or $107,000 whichever is greater. Accredited investors are not limited in the amount they can invest.
How do I calculate my net worth?
Calculating net worth involves adding up all your assets and subtracting all your liabilities (excluding the value of the person’s primary residence). The resulting sum is your net worth.
What are the tax implications of an equity crowdfunding investment?
We cannot give tax advice, and we encourage you to talk with your accountant or tax advisor before making an investment.
What are the tax implications of an equity crowdfunding investment?
We cannot give tax advice, and we encourage you to talk with your accountant or tax advisor before making an investment.
Who can invest in a Regulation CF Offering?
Individuals over 18 years of age can invest.
What do I need to know about early-stage investing? Are these investments risky?
Investing in startups and small businesses is inherently risky and standard company risk factors such as execution and strategy risk are often magnified at the early stages of a company. In the event that a company goes out of business, your ownership interest could lose all value. Furthermore, private investments in startup companies are illiquid instruments that typically take up to five and seven years (if ever) before an exit via acquisition, IPO, etc.
When will I get my investment back?
Wink Robotics Inc. is a privately held company, and its shares are not traded on a public stock exchange. As a result, the shares cannot be easily traded or sold. As an investor in a private company, you typically receive a return on your investment under the following two scenarios: The company gets acquired by another company. The company goes public (makes an initial public offering on the NASDAQ, NYSE, or another exchange). In those instances, you receive your pro-rata share of the distributions that occur, in the case of acquisition, or you can sell your shares on the exchange. It can take 5-7 years (or longer) to see a distribution or trading, as it takes years to build companies. In many cases, there will not be any return as a result of business failure. Investments in private placements and start-up investments in particular are speculative and involve a high degree of risk, and those investors who cannot afford to lose their entire investment should not invest in start-ups. Companies seeking startup investments tend to be in earlier stages of development, and their business model, products and services may not yet be fully developed, operational or tested in the public marketplace. There is no guarantee that the stated valuation and other terms are accurate or in agreement with the market or industry valuations. Additionally, investors on Regulation CF offerings will receive securities that are subject to holding period requirements. The most sensible investment strategy for start-up investing may include a balanced portfolio of different start-ups. Start-ups should only be part of your overall investment portfolio. Investments in startups are highly illiquid and those investors who cannot hold an investment for the long term (at least 5-7 years) should not invest.
Can I sell my shares?
Shares sold via Regulation Crowdfunding offerings have a one-year lock up period before those shares can be sold under certain conditions.
Exceptions to limitations on selling shares during the one-year lock up are transfers:
- to the company that issued the securities; - to an accredited investor; - to a family member (defined as a child, stepchild, grandchild, parent, stepparent, grandparent, spouse or spousal equivalent, sibling, mother-in-law, father-in-law, son-in-law, daughter-in-law, brother-in-law, or sister-in-law, including adoptive relationships.); - in connection with your death or divorce or other similar circumstance;
What happens if a company does not reach their funding goal?
If a company does not reach their minimum funding goal, all funds will be returned to the investors after the closing of their offering.
How can I learn more about a company's offering?
All available financial information can be found on the offering pages for the company’s Regulation Crowdfunding offering.
What if I change my mind about investing?
You may cancel your investment at any time, for any reason until 48 hours prior to a closing occurring. If you have already funded your investment and your funds are in escrow, your funds will be promptly refunded to you upon cancellation. To submit a request to cancel your investment please email info@luumlash.com.

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