Crunch #014

Your weekly dose of winning startups

Trevor here. Back with another edition. We have super exciting and vibrant startups today — Here we go!

🇺🇸 luminDX: Medical software for identifying skin conditions. Designed to help doctors. The software runs an image through a large database of conditions and finds diagnoses. (Founded 2017, prev funding: $2.4M seed)

According to the company, 2.3 billion people look for help with skin issues each year. — But 50% of skin issues are misdiagnosed.

🇪🇪 Cachet: Insurance marketplace for the gig and sharing economy service providers. (Founded 2018, prev funding: €1.5m seed)

“The gig economy is snowballing, but financial services are not adjusting fast enough.”— Founder, Hedi Mardisoo, (Techstars “20)

🇨🇦 basedash: Edit your database with the ease of a spreadsheet. safely edit production data across your team. No code required. (Founded 2019, prev funding: $125k seed)

🇺🇸 EasyClout: Social media management and growth platform. Watch your customer base grow with our publishing, analytics, and activity features. (Founded 2020, prev funding: bootstrapped)

“I have a web development background — and I don’t get why HootSuite, Buffer, etc don't offer more for less. So, I decided to take matters into my own hands and come up with better solutions.” — Founder, Bill Hinostroza

🇺🇸 DigitalBrain: Get through your support tickets twice as fast. DigitalBrain is an external layer on top of existing helpdesks. (Founded 2019, prev funding: $3.4m seed)

🇫🇮 Flowrite: Supercharge your everyday writing tasks by turning words into ready-to-send emails, posts, and more. (Founded 2020, prev funding: $660k pre-seed)

“We are passionate about creating software that has a positive effect on everyday work. Read more here.“— Co-founder, Aaro Isosaari

🇫🇷 Photoroom: Automatically removes background for images. AI-powered marketing images with your phone. (Founded 2019, prev funding: $125k seed)

“I left GoPro a little more than a year ago and decided to go back to school for a machine learning online course. During the class, I developed a few prototypes mixing machine learning and mobile apps.

Out of the class, I met with Eliot, my partner, who is a machine learning expert. We created the first version of PhotoRoom in two weeks. The first version was a bit rough around the edges but already used a Core ML machine learning algorithm to remove the background.” — Founder, Matthieu Rouif

🇺🇸 Extract text, photos, and signatures from any document. Say no to manual data entries. Try out the data extraction and face recognition demos here. — (Founded 2020, prev funding: bootstrapped)

🇨🇦 HyperCharts: Business and financial metrics of popular public companies. $6.8k/mo — (Founded 2019, prev funding: bootstrapped)

“I needed a way to visualize the financial metrics of the public companies I was investing in” — Moe Salih

🇸🇪 Mathquizily: Personalized math tests. Map your math skills with tests and step-by-step solutions. (Founded 2019, prev funding: bootstrapped)

“The problem I want to solve is the knowledge gaps in the mathematics of students that are formed over the years.

With the help of personalized math tests, students will be tested on the things they have difficulty with. This approach helps to close these knowledge gaps.” — Founder and math teacher, Edin Adilagic

I spoke with Edin earlier, and he mentioned he’s actively looking for investors. Let’s help a local Swedish math teacher actualize his dreams.

🇦🇹 Shark Bike: Combines the advantages of electric cars and e-bikes in one product, the SHARK-Bike. (Founded 2017, prev funding: bootstrapped)

“After pitching the SHARK-Bike concept at the FH CAMPUS VIENNA — we received a golden ticket to the STARTUP-CORNER with access to a great workshop and even an office space.

Shortly after I recruited the first team members and together we started working on the prototype of the SHARK-Bike.” — Founder, Paul Japek

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Startups Crushing It! is a premium newsletter about early-stage (before series A) technology startups. I publish the insights each Tuesday or Friday.

I look for strong positive signals using the FPTM model: Founders — Product — Traction — Mission.

I interview the founder(s), toy around with products, crunch numbers, and based on that, I decide which startups to feature.

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