One Acquisition. Multiple Revenue Streams. A Cash Machine Running From Your Laptop.
Acquire novel AI Digital Twin software with the potential to become a highly valuable recurring-revenue asset across multiple industries.
Own the technology and IP outright, then monetize it through enterprise licensing, recurring software fees, usage-based models, and strategic commercial partnerships.
The software is highly scalable and does not require a large physical operation, extensive facilities, or a location-dependent business infrastructure to generate revenue. With the right commercialization strategy, the business can be operated with a lean team while serving customers across multiple markets and countries.
The same software can be commercialized across pharma, healthcare, insurance, genomics, digital health, and other high-value markets—creating multiple revenue channels from one proprietary technology.
Acquire once. License repeatedly. Scale globally. Build substantial recurring revenue without the overhead of a traditional physical business.
Acquire. Liscence. Scale .
Novel AI Digital Twin Technology / Software.
Acquire proprietary AI Digital Twin longevity technology your competitors cannot build in-house. Own the IP outright. Deploy across any industry. Generate recurring revenue by licensing to multiple verticals simultaneously.
Sell the Technology to an Entire Industry
If you are an unspecialized buyer looking to generate a cash machine without having to build the technology yourself, Loju Longevity offers that opportunity.
License the platform to longevity companies, clinics, physicians, laboratories, and health platforms that need AI Digital Twin capabilities for their own customers. Each licensee pays recurring fees. You own the asset. Your competition spends years trying to replicate what you already control.
Watch the Technology Demonstration: " rel="nofollow" target="_blank">https://youtu.be/7s51zpAq21U
See the computational architecture, AI Longevity Digital Twin, and Biomedical Reasoning Engine in action—showing how the system ingests multimodal biomedical data and generates continuously updated, individual-level outputs in real time.
WHAT YOU ACQUIRE
The IP & Assets:
The competitive advantage: This technology took years to develop because it required expertise most companies don't have: deep biomedical science + advanced AI + systems architecture. Acquiring it means acquiring years-ahead advantage in one transaction.
Internal development equivalent: 3–5 years and $5M–$15M+ in R&D. Acquisition gives you months.
WHY THE TECHNOLOGY MATTERS
The AI Digital Twin does something most AI cannot: it models individual human health as a dynamic, interconnected system—not isolated datasets.
It understands how a specific person's body works, how they'll respond to treatment, what their health trajectory looks like, and what interventions matter most for them. It continuously updates as new biomedical information becomes available.
That capability is worth a fortune in multiple industries—because almost no one has it.
WHERE THIS TECHNOLOGY WINS
Pharmaceutical companies could deploy it to predict which patients will respond to a drug and optimize clinical trial design.
Insurance companies could use it to predict health trajectories and prevent costly interventions.
Hospitals could personalize treatment plans and reduce readmissions.
Digital health platforms could offer it to users who want personalized health insights.
Genomics companies could use it to interpret genetic data at the individual level.
Medical device manufacturers could enable personalized diagnostics and treatment recommendations.
The technology isn't confined to one industry. It's foundational AI infrastructure for anyone who needs to understand individual human health at scale.
The companies who need this most:
Each of these industries has buyers with budgets and urgency. Most lack this capability in-house.
HOW THE BUYER MAKES MONEY
The buyer acquires the technology once and owns it outright. They deploy it to any company that will pay to use it. Once deployed, there's minimal additional cost—the technology scales infinitely.
This isn't a one-time license fee model. The buyer charges recurring deployment fees because the technology enables recurring value for their customers. A pharma company uses it to run clinical trials continuously. An insurance company uses it for ongoing member management. A hospital uses it for every patient admission.
The buyer's customers pay for continuous access. The buyer's margin is 70–90%+ because the marginal cost of serving the next customer is nearly zero.
Scale example: If the buyer licenses the technology to just 50 customers at $50K per month each, that's $2.5M monthly recurring revenue. At 100 customers, it's $5M monthly. This technology pays for itself in months, not years.
Revenue model options:
WHY THIS ACQUISITION MATTERS
Defensible moat. The technology is built on proprietary biomedical datasets and novel AI architecture. It's not something a competitor can reverse-engineer or replicate quickly. The datasets took years to assemble. The algorithms took deep biomedical expertise to develop. Once acquired, the buyer owns this advantage permanently.
Time-to-market advantage. Building equivalent technology internally would take 3–5 years and cost $5M–$15M+. The buyer acquires it in one transaction and deploys in months. In fast-moving AI markets, years matter.
Recurring, high-margin revenue. Because the technology is deployable to unlimited customers with minimal additional cost, the buyer's gross margins will be 70–90%+. Revenue scales with each new customer deployment. This is the kind of unit economics that PE firms love and strategic acquirers want to own.
Competitive differentiation. Any buyer who acquires this technology immediately differentiates from competitors. Pharma companies can personalize drug trials. Insurance companies can predict health trajectories others can't see. Hospitals can optimize treatment in ways that reduce costs and improve outcomes. Digital health platforms can suddenly offer AI capabilities that seemed out of reach.
Multiple deployment paths. The buyer doesn't have to choose between verticals. They can deploy the technology to pharma one month, insurance the next, and hospitals the month after. The same underlying technology serves completely different industries. This optionality reduces risk and increases revenue potential.
Regulatory readiness. The platform has been architected with awareness of future regulatory pathways relevant to diagnostics and clinical decision support. It is positioned to support regulatory alignment as part of a future product roadmap, reducing compliance risk for acquirer deployments.
WHO SHOULD ACQUIRE THIS
Strategic buyers with distribution: Large pharma companies (Pfizer, Merck, J&J, Roche) have sales teams, customer relationships, and budgets to deploy and license this technology immediately. Same with health insurers (UnitedHealth, Cigna, Anthem) and hospital networks (CVS Health, Kaiser). They acquire the technology and immediately integrate it into existing workflows.
Tech companies entering healthcare: Digital health platforms (Teladoc, Amazon Clinic, Apple Health) and genomics companies (Helix, 23andMe) need differentiated AI capabilities to compete. Acquiring this technology lets them offer personalized health intelligence that competitors lack.
Private Equity looking for recurring revenue: This is the ideal PE acquisition—novel technology with recurring revenue potential, low marginal cost, and multiple deployment paths. A PE firm acquires, deploys to 50–100 customers over 3–5 years, and exits at a 6–8x EBITDA multiple built on recurring revenue.
Technology companies investing in AI infrastructure: AI platforms and data science companies need healthcare-grade reasoning capabilities. This becomes a foundational layer for their AI stacks.
The buyer who moves first captures the market. This isn't a feature that gets copied next year. It's foundational AI that takes years to replicate. Whoever owns it first owns a structural advantage.
THE DEAL
What transfers:
Timeline:
Deal structure: Asset sale transferring complete ownership and commercial rights.
WHY THIS CANNOT BE BUILT INTERNALLY
Acquiring it is faster, cheaper, and lower-risk than building it.
ABOUT THE FOUNDER & TEAM
Dr. Ola Abdalla – Founder & CEO, Loju Longevity
Dr. Abdalla is a scientist, innovator, and entrepreneur with multidisciplinary expertise spanning artificial intelligence, computational biology, longevity science, biomedical innovation, and business development.
Education:
Professional Experience:
LinkedIn: Dr. Ola Abdalla
The team brings rare combination of deep biomedical science, AI/ML expertise, and commercial experience—critical for both the technology's development and successful buyer integration.
THE BOTTOM LINE
This is an acquisition of novel biomedical AI technology that a strategic buyer can deploy across multiple industries to build recurring revenue at 70–90%+ margins.
The buyer acquires:
The technology is not replicable quickly. The time-to-market advantage is measured in years, not months. Building equivalent capabilities internally would cost $5M–$15M+ and take 3–5 years. Acquisition gives you months.
The buyer who acquires this first captures the market in personalized AI for health.
NEXT STEPS
Confidential discussions with qualified buyers are invited. Interested parties are welcome to contact and begin a confidential conversation.
For more information or to request a confidential discussion.
Watch the technology demonstration: " rel="nofollow" target="_blank">https://youtu.be/7s51zpAq21U
Intellectual property status
Other forms of protection
Novel proprietary technology protected through copyright, confidential know-how, proprietary algorithms, trade secrets, source code, datasets, and technical knowledge. The technology is not currently patented. Its value is protected primarily through proprietary know-how, secrecy, copyright, and ownership of the underlying software and intellectual property.
Current development status
Commercially available technologies
Desired business relationship
Technology selling
Dr. Ola Abdalla is a scientist, entrepreneur, and business strategist with 8+ years of experience bridging scientific innovation and business strategy across Japan, New Zealand, and international markets. Holding a doctoral degree from Hokkaido University — one of Japan's top 10 universities and ranked among the top 200 globally — and a business education, she brings a rare combination of deep expertise in genomics, bioinformatics, and longevity science with sharp business strategy.
Dr. Ola's career has spanned continents and disciplines. From conducting genetics and bioinformatics research as a Japanese Government Scholar to leading joint collaborations between Hokkaido University and the University of Auckland, Dr. Ola's work has produced peer-reviewed publications and earned one of Japan's most competitive academic fellowships
Beyond research, Dr. Ola has leveraged a strong business education to contribute to open innovation and technology strategy at a multinational corporation in Tokyo, identifying emerging technologies and developing new business models that drive commercial outcomes across international markets
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