MD746398

This healthcare technology startup is revolutionizing ultrasound by turning it into a robust tool for early disease detection and remote monitoring through AI-driven image enhancement. By making high-quality imaging accessible outside hospitals, they address the growing demand for remote patient care.

Their strong partnerships with industry leaders like Roche and Mayo Clinic further validate their approach. With a projected $117 billion remote monitoring market and plans to expand into AI-driven biomarkers, this company is primed for rapid growth, offering investors a chance to support transformative technology with high market potential and scalable impact.

Overview

Industry: AI-Enhanced Ultrasound Imaging
Founding Year: 2022
Location: USA
Mission: To optimize access to healthcare by converting everyday ultrasound into a powerful data source, improving early disease detection and preventive care globally.
Unique Value Proposition: AI-powered models enhance ultrasound imaging, providing expert-level scan resolution, tissue contrast, and noise reduction without the need for expensive new hardware.

Problem & Solution

Problem: Limited access to high-quality imaging data hinders preventive care and early diagnosis, leading to costly hospital over-admissions and delayed drug development.

One of healthcare’s biggest challenges is the lack of diverse, continuous data on disease progression, especially in medical imaging. This data gap impedes preventive monitoring, clinical trials, and personalized medicine, leading to $50B in wasted research and $8M in daily drug revenue loss. It also contributes to $30B in over-admissions to hospitals. Current ultrasound technology is limited by trade-offs in image quality, cost, and mobility, restricting its use for early diagnosis. Integrating mobile ultrasound can bridge this gap, enhancing early disease detection.
Solution: AI-driven ultrasound technology that enhances image quality and provides actionable data on disease progression, enabling remote monitoring and early intervention outside traditional clinical settings.

Conventional ultrasound faces limitations in image quality, cost, and mobility, but this company is transforming it into a powerful tool for early-stage disease detection. Their AI-powered platform enhances traditional mobile ultrasounds, enabling even non-experts to capture high-quality images and track disease progression outside of hospitals. Their patented technology detects subtle tissue changes and provides real-time navigation for optimal imaging, making ultrasounds accessible anywhere. Beyond healthcare, the system generates valuable data for pharmaceutical trials, optimizing drug development with real-world patient insights.

Market Potential

Target Market: Imaging as a biomarker and preventive remote patient monitoring.
Market Size:

‍Total Addressable Market (TAM): $117 billion for remote patient monitoring by 2028.

The remote patient monitoring market is projected to reach USD 117 billion by 2028 from USD 28.5 billion in 2022, at a CAGR of 10.4%. the global biomarkers market is projected to reach $97.3 billion by 2027.
‍
‍Serviceable Available Market (SAM): $5 billion for remote monitoring technologies.

The SAM is USD 5 billion, remote monitoring technologies that are used in hospitals at home, remote primary care services, pharmacies, and first aid systems.
‍
‍Serviceable Obtainable Market (SOM): $1 billion for ultrasound imaging in preventive monitoring.
‍
Growth Rate: CAGR of 10.4% for the remote patient monitoring market.
Market Trends:

- Rise of Remote Patient Monitoring (RPM).
- Reducing hospital over-admissions through early detection.
- Increasing demand for early disease detection.
- Growing importance of real-world data in drug development.
Advantage:

→ Proactive Patient Management: The platform continuously monitors patients’ health, identifying early signs of deterioration and allowing for timely intervention, preventing unnecessary hospitalizations.
‍
→ Enhanced Diagnostic Capabilities: Its advanced image processing algorithms detect subtle disease markers, enabling earlier diagnoses and more effective treatment plans.
‍
→ Accelerated Drug Development: High-quality ultrasound data supports the creation of new imaging biomarkers and clinical trials, speeding the delivery of life-saving therapies to market.
‍
→ Improved Healthcare Efficiency: By reducing hospital admissions and enabling remote monitoring, the company enhances healthcare efficiency and cost-effectiveness.
Primary Customer Segments: The target customers encompass various stakeholders in healthcare who crave high-quality, diverse, and frequent data on early-stage disease progression:

Pharmaceutical Companies: Research and Development teams leverage this data to optimize drug development by identifying promising candidates earlier and tailoring therapies with greater precision.

Research Hospitals: Clinicians and researchers utilize the data to accelerate personalized medicine approaches and improve grant competitiveness.

Retail Care / Clinics / Pharmacies: Retail care centers, pharmacies, and clinics that provide remote care, and hospital at-home services for their patients, customers and offer new care services targeting mass market adoption.

Within these organizations, we target key decision-makers like Heads of Research & Development, Clinical Research, and Innovation, as well as leading physicians and researchers.

Product / Service

Core Features:

AI-Driven Imaging and Interpretation: The company's advanced AI guides users in real-time to capture and interpret ultrasound images, enabling even non-experts to generate high-quality images, lowering access barriers.

‍Data-Driven Disease Monitoring: Their system produces real-time data on disease progression, enhancing patient care and providing insights for research and pharmaceutical trials.

‍High-Quality Image Enhancement: Patented image enhancement technology improves image quality, resulting in more accurate diagnoses, better patient outcomes, and reduced healthcare costs.
Technology Stack: Built on AWS infrastructure with AI/ML frameworks like TensorFlow and PyTorch for advanced image processing and machine learning.
Development Stage: MVP developed, with over 5,000 scans conducted in collaboration with major healthcare partners.
Intellectual Property: 1 patent on image enhancement, 3 pending patents for AI-driven navigation and tissue characterization.
Product Roadmap:

Year 1: AI-driven tissue characterization, biomarker extraction, GenAI for synthetic ultrasound data.
Year 2: Next-gen cognitive ultrasound imaging technology, clinical validation and integration.

Business Model

Revenue Model:

Licensing of AI-enhanced ultrasound technology to healthcare providers.
Revenue from a database of medical images generated outside hospital settings.
Pricing Strategy:

Future revenue model is based on a B2B licensing approach. They plan to generate income through licensing their ultrasound technology to pharmaceutical companies, retail care centers, pharmacies, and hospitals, with fees ranging from $15-30 per session. Additionally, they aim to create a vast medical image database, projecting over 10 billion images by 2025, which will be sold to support drug development. This dual revenue strategy, though not currently generating revenue, positions the company for substantial growth as they scale.
Sales Channels: Strategic partnerships with medical equipment distributors and pharma companies.
Customer Acquisition Strategy: Focused on content marketing, digital marketing, and participation in industry events to build brand awareness and generate leads.
Customer Retention Plan: The company plans to implement customer success teams for ongoing support and enhance the platform based on user feedback and market trends. They will offer comprehensive training and resources to maximize product usage, while loyalty programs will incentivize customer engagement and referrals. Additionally, they aim to actively gather customer feedback through surveys and other channels to refine the product and improve the overall experience. These plans are designed to foster strong relationships and ensure continuous improvement as the platform evolves.

Financials

Current Status:

Pre-revenue with a burn rate of $15,500 per month and an 8-month runway.
$550k raised to date with an additional $140k in grants.
Use of Funds:

60% Product Development
20% Market Research
20% Regulations, Administrative
Projections:
‍
1-Year ARR: $4.5 million.
3-Year ARR: $50 million.
5-Year ARR: $100 million with a 40% profit margin.
Key Metrics: CAC (Customer Acquisition Cost) of $4,500, LTV (Lifetime Value) of $15,600, Gross Margin of 55%, and Net Profit Margin of 35%.

Team

Founders:

CEO: With over 20 years of experience in Healthtech and deep-tech, this executive has held leadership roles at major corporations, managing emerging technologies and expanding into new markets. He built teams, developed connections, and successfully integrated new technologies into product portfolios. Recognized with numerous awards, including the Best Innovation in Cleantech (UNIDO), Best AI Solution in Building Technology, and Top 25 Innovations of Living and Working (Accenture), his expertise spans sustainable technologies, energy management, and AI, further solidified by speaking engagements at prominent global events.
‍
CTO: Over 20 years of experience pioneering deep-learning AI systems for ultrasound imaging at major universities. He has received prestigious awards, including the Women's Healthy Institute Innovative Research Award and the North American Spine Society Fellowship. His research, published in 23 journals, spans over 30 peer-reviewed conferences and has led to 19 national and international student awards under his supervision. Additionally, he holds three patents, solidifying his expertise in medical imaging and AI innovation.
Key Team Members: Includes data science and radiology experts, with plans to expand the team significantly post-funding.
Advisors: Experienced professionals from top medical institutions and tech companies.Their advisors are experienced radiologists, ER doctors, and regulation experts from Texas Medical Center, UCLA School of Medicine, and HCA Healthcare.
Hiring Plans: With the funding they are planning to hire 3 Lead AI Engineers, 4 AI Engineers, 3 Full Stack SW developers, 2 Biomedical Engineers, and 2 Sales Engineers.

Competitive Analysis

Direct Competition Strengths & Weaknesses: Competitors in this space have notable strengths, including strong brand recognition, financial resources, large teams, and established sales networks. However, their technologies are primarily restricted to hospital use by doctors, with low image quality and no AI-driven image enhancement. They are mainly used for late-stage disease monitoring and lack advanced capabilities like AI-driven tissue characterization and comprehensive data analytics. Additionally, their reliance on third-party applications for image analysis limits functionality and control, preventing them from generating the actionable insights that more integrated solutions can offer.
Indirect Competition: Indirect competitors provide alternatives to ultrasound imaging or focus on other aspects of patient care. These include other imaging technologies like MRI, CT, and PET scans, which offer detailed diagnostics but are less portable. Telehealth companies focus on remote patient monitoring and diagnostics, offering virtual healthcare solutions. Additionally, Electronic Health Record (EHR) providers integrate healthcare data across systems, facilitating coordinated care but lacking the direct imaging capabilities offered by ultrasound-based technologies. These solutions address different facets of healthcare but do not directly compete in the same imaging space.
Competitive Advantage: Patented image enhancement technology, AI-powered image interpretation, and a focus on making ultrasound accessible in remote locations.

This company distinguishes itself from competitors through its patented image enhancement software, which improves ultrasound quality nearly tenfold. Its AI-powered image interpretation generates critical data on disease progression, making ultrasound accessible not only in hospitals but also in homes and remote locations. Their deep learning algorithms elevate risk assessment outside traditional settings, while the image enhancement system provides expert-level resolution, tissue contrast, and noise reduction—without requiring costly new hardware. This approach revolutionizes ultrasound imaging, offering a more versatile and affordable solution for early disease detection.
Barriers to Entry: Regulatory hurdles, high development costs, the need for a robust distribution network, and challenges with talent acquisition.

Traction

Milestones Achieved: Partnerships with Roche, Mayo, and Memorial Sloan Kettering; release of AI-driven navigation and image enhancement products.
Awards and Recognitions: UN WIPO Global Awards Winner, AARP AgeTech Winner, Bayer G4A Winner, AI Pharmaceuticals Innovation Competition Winner, CTA Wireless Foundation runner-up.

Risks & Mitigation

Market Risks: Regulatory changes and economic downturns impacting healthcare spending.
Operational Risks: Challenges in talent acquisition, data security, and product development delays.
Mitigation Strategies: Diversification, strategic partnerships, and comprehensive risk management processes.

Funding Requirements

Amount Being Raised: $5 million
Use of Funds:

30% Product Development
20% Marketing and Sales
30% Hiring
20% Regulatory and IP-related expenses
Expected Runway: 18 months
Previous Funding Rounds:

Amount Raised: $550k
Investors: 2 Venture Capital Firms, Angel Investor
Valuation: $15M Pre-money

Exit Strategy

Potential Exits: The company's exit strategy focuses on acquisition within 4-5 years, targeting major healthcare technology players seeking to enhance their AI and imaging capabilities. Potential acquirers include industry giants in medical imaging, who could leverage the company’s decentralized ultrasound technology to expand into primary and rural care. This AI-enabled ultrasound platform aligns with the future of healthcare, which is moving toward continuous monitoring and early intervention. As the demand for accessible, data-driven diagnostics grows, the company is well-positioned to offer revolutionary solutions for a decentralized healthcare landscape.
IPO: Not considered a suitable short-term exit strategy due to current market conditions.
Other: To maximize joint ventures, the company could collaborate with healthcare systems on population health management and new care models. Partnering with pharmaceutical companies would support the development of ultrasound-based diagnostic tools and therapeutic interventions. Additionally, teaming up with technology firms specializing in AI, data analytics, or cloud computing could enhance their capabilities, helping improve imaging quality, data processing, and scalability. These partnerships would expand the company’s reach and further strengthen its technological and clinical impact.
Expected Timeline: 2028