5 Interesting Startup Deals You May Have Missed In December: A Hospital-Grade Wireless Heart Monitor, AI-Designed Proteins For Manufacturing, And More

This is a monthly column that runs down five interesting startup funding deals every month that may have flown under the radar. Check out our November entry here.

This month, funded startups that caught our eye included a company aiming to make a better wireless monitor for heart disease, another using AI-designed antibodies for home health tests, a startup using AI to improve airplane turnaround times, and a company developing AI-designed proteins for industrial, manufacturing and defense purposes.

$29M for at-home hormone health testing

, a startup that offers popular at-home fertility tests, this month raised $29 million in Series B funding to expand its platform beyond fertility monitoring for women trying to conceive, to a broader slate of at-home diagnostics.

The Palo Alto, California-based startup was founded in 2015. Since 2021, it has analyzed more than 30 million fertility hormone data points, per the company. That data will be useful as it aims to use its new funding to expand beyond fertility monitoring to a range of hormone-related health markers.

Key to that expansion is the development of AI-engineered antibodies, or synthetic proteins created by computer models that predict how antibody molecules should fold and bind to specific targets.

鈥淲e predict how proteins fold in 3D, design synthetic antibodies using AI, and test millions of variants virtually before making a single one in the lab,鈥� Inito co-founder and CTO via email. 鈥淭his produces antibodies that are far more sensitive, consistent, and stable than anything developed through traditional methods.鈥�

Inito says that innovation will enable it to build new, accurate at-home health tests for a wider range of biomarkers. This capability is central to the startup鈥檚 plan to grow from fertility tracking into a broader at-home health diagnostics platform that could be used to track pregnancy progression, menopause, broader endocrine markers like testosterone, and other hormonal health indicators.

鈥淭he endgame is to redefine diagnostics altogether,鈥� CEO and co-founder told TechCrunch. 鈥淚f you want to understand what鈥檚 happening inside your body at every life stage and health need, you shouldn鈥檛 be limited by clinic appointments, lab schedules, or rigid testing systems. You should be able to measure, track, and get insights about your body from home, with lab-grade confidence.鈥�

and led the company鈥檚 Series B funding. The startup has now raised $42.5 million total, .

$26.6M for smoother airport operations

A startup that promises to make air travel less of a headache is always going to catch our attention. So it was with , a Zurich-based startup that this month raised $26.6 million in Series B funding for its AI-driven airport operations platform.

The company says its technology 鈥� already in use at New York鈥檚 JFK, London鈥檚 Heathrow, Dubai International and Toronto Pearson airports 鈥� helps to streamline the commercial aircraft turnaround process at major air travel hubs, many of which are facing increased traffic, tighter operating margins and staffing constraints.

A portion of Assaia鈥檚 new capital will be used to further develop StandManager, its AI software module that helps optimize gate and stand assignments before aircraft land, the company says.

Assaia鈥檚 Series B was led by , alongside existing investors. 鈥淲e focus on investing in resilient business models that demonstrate a distinct technological advantage, and Assaia exemplifies that,鈥� , managing partner at Armira, said in a statement. 鈥淚ts AI platform is already transforming airport operations and helping the aviation industry navigate some of its most complex challenges.鈥�

$15M for AI-designed proteins for manufacturing

announced $15 million in new funding this month, promising to manufacture novel new materials using AI-developed proteins and biological processes.

The Menlo Park, California-based startup says it has raised $64 million in total funding, including this latest round, which was led by with participation from new and existing investors including , , , , , and

Aether says it combines 鈥減urpose-built AI and high-throughput robotics to design proteins that act like molecular assemblers, tiny machines that build one atom at a time.鈥�

These 鈥渘anoscale machines have the precision and sophistication of massive chemical factories, but at a fraction of the size, enabling Aether to make new products faster, more affordably, and more sustainably,鈥� according to the company.

Its first product is RapidPrint, which it describes as a high-performance 3D printing polymer filament line that uses AI-optimized materials to enable dramatically faster manufacturing of aerospace, defense and industrial parts.

The company says overall, it has developed seven new classes of proteins that have the potential to be used in defense, aerospace, pharmaceutical manufacturing, carbon capture and other applications.

鈥淥ne of the things we have got very good at is targeting a novel molecular species and making it very quickly,鈥� Aether CEO and founder told .

Tribe Capital Chairman said his firm invested because it was excited about the real-world applications for Aether鈥檚 technology. 鈥淲e鈥檝e seen many AI companies focus on discovery, but no one has taken the leap from designing proteins to delivering physical, market-ready products until Aether,鈥� he said in a funding announcement. 鈥淎ether is proving that its approach isn鈥檛 just innovative in theory; it鈥檚 faster, more cost-effective, and higher-performing than traditional methods, setting the standard for what AI-driven chemistry can achieve in the real world.鈥�

$14M for a wireless heart monitor

Heart disease is ., claiming nearly a million American lives in 2023, per the . But despite the disease鈥檚 prevalence, accessible technology to monitor for heart issues is not as common as you may think.

, a San Francisco-based startup that offers a wireless heart monitor that it says offers hospital-grade monitoring at home, this month announced a $14 million Series A. The company says its product offers patients and cardiologists hospital-level heart data from anywhere.

鈥淎t home, most devices track heart rate rather than the electrical rhythm,鈥� the company said in a press release. 鈥淗eart rate alone can鈥檛 catch many arrhythmias or the subtle changes that signal rising risk. In hospitals, wired telemetry is bulky and brief, and single-lead patches often miss intermittent events. The result is a system where patients take devices off, doctors order repeat tests, and heart disease continues to claim millions more lives.鈥�

The company says its device is used in 75 cardiology units and by thousands of patients a month, and that it鈥檚

Wearlinq said it will use the new funding to 鈥渄ramatically scale鈥� and expand its reach into hundreds of additional clinics. Its funding was led by .

A long list of other investors participated: , , , , , , , , , , and Alongside the equity round, the company also raised $5 million in venture debt.

$6M to analyze commercial real estate portfolios in minutes

Commercial real estate doesn鈥檛 immediately strike us as an area ripe for innovation, which helps to explain why investment into proptech startups overall has plummeted in recent years.

But given the trillions of dollars held in commercial real estate portfolios, a platform that promises to drastically streamline real estate investments and financial modeling does seem like a savvy bet.

To that end, , a London-based startup used by commercial real estate investors for financial modeling and analysis, this month announced $6 million in seed funding to expand into the massive U.S. commercial real estate market. The company says its platform has already been used to analyze $70 billion worth of investment opportunities in the U.K. and Europe. It鈥檚 now hoping to get a foothold in the estimated $22 trillion U.S. commercial real estate market.

Its seed round was led by , with participation from , , and 鈥渟everal angel investors and property sector veterans.鈥�

Built AI says its platform uses machine learning to extract and analyze building data to help clients manage their portfolios and underwrite new investment opportunities. The platform can analyze single properties or entire portfolios, and looks at variables such as lease terms, valuation, tenant profiles and local market data. It reduces analysis time by 90%, from hours or days to minutes, according to the company.

The company was founded in 2020 by , who previously held roles at , and and , previously director at . It has raised $8.5 million to date, .

鈥淩eal estate is the world鈥檚 largest asset class and yet the tools used to appraise deals have barely evolved in the last 40 years. Billions of dollars worth of investment deals are still screened every year using outdated, error-prone processes leading to over $185 billion in annual losses because of incorrect valuation metrics or missed opportunities,鈥� Lempert, the company鈥檚 CEO, said in a statement. 鈥淕enerative AI is becoming increasingly embedded in financial decisions, to translate data at scale and automate underwriting,鈥� he said.

The company鈥檚 client list includes real estate giants , and .

鈥淭he future of software requires three essential attributes: domain expertise, AI skills, and ingenuity. These founders have all three and seek to fundamentally reimagine the real estate investment process,鈥� , co-founder and general partner of Work-Bench, said in a statement.

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