Nextnet · GenEdit
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Nextnet
By NextnetNextnet is an AI-native knowledge platform for life sciences and healthcare teams. Our Copilot assistants and Explorer engine help users ask questions, visualize, and share biomedical insights- powered by the world’s largest semantic web of health data.
- Stage
- In production
- Industries
- Healthcare
- Deployment
- Cloud (SaaS)
Why it is worth it
Nextnet is pioneering a radical departure from traditional data platforms. We're not a data broker or aggregator - we're building an intelligent knowledge ecosystem that fundamentally reimagines how life science enterprises manage, connect, and leverage their intellectual capital. At the core of our innovation is a sophisticated semantic knowledge web powered by advanced language model technologies and knowledge graphs. And we've developed a proprietary ontological framework that: -Unifies open-source biomedical ontologies (including gene, disease, medical subject headings, and UMLS lexicon) through granular semantic mapping -Creates a comprehensive, interconnected "source of truth" that enables unprecedented data connectivity at enterprise scale -Empower life sciences knowledge workers by essentially providing them with a grammatical structure (ontology) that makes their data intelligible to them while simultaneously obfuscating data they are now allowed to see according to rules they impose. Our platform transcends traditional knowledge management by transforming institutional memory into a living, adaptive intelligence. Nextnet's AI continuously analyzes historical data, generating novel insights and connecting past research with emerging discoveries. Imagine a system where a new team member can instantly access and contextualize decades of organizational knowledge, dramatically accelerating innovation and reducing redundant research. Here is a social media post that we made on this a couple of months ago. Key differentiators from our competitors: -Semantic Intelligence: Advanced ontological mapping that creates meaningful connections across disparate data sources -Adaptive Institutional Memory: AI-powered knowledge synthesis that turns historical data into actionable insights -Strict Data Governance: Comprehensive control mechanisms that protect sensitive information while maximizing knowledge sharing
- Nextnet addresses a critical and persistent pain point in the life sciences industry: the fragmentation of biomedical knowledge and data.
- Enterprises across the sector - whether in research, clinical development, or commercialization - struggle with disjointed information ecosystems. Knowledge is scattered across incompatible taxonomies, siloed repositories, and legacy systems that lack semantic alignment. This makes it incredibly difficult for teams to search, connect, and act on scientific insights in a cohesive, scalable way.
- While initiatives like UMLS, OBO Foundry, and MeSH have made strides in standardization, their scope is limited and integration with modern AI systems remains minimal. Meanwhile, the proliferation of open data repositories has outpaced the infrastructure needed to meaningfully connect and query them, resulting in duplicated effort, incomplete discovery, and wasted R&D resources.
- This semantic disunity directly undermines the effectiveness of AI and machine learning in enterprise use cases. Applying advanced models to fragmented or misaligned datasets produces biased, unreliable insights - limiting ROI on AI investments.
- Nextnet solves this by creating a semantically unified, AI-native knowledge infrastructure for the life sciences.
- Our platform integrates LLMs and proprietary ontologies to organize, relate, and surface biomedical knowledge in a way that’s interoperable, accurate, and actionable. This enables faster and more reliable discovery, insight generation, and decision-making across key enterprise functions:
- R&D and Early Discovery: Rapid hypothesis testing and literature review
- Clinical Development: Semantic linking of trial data, biomarkers, and outcomes
- Manufacturing & Supply Chain: Mapping of scientific insights to operational decisions
- Commercial Strategy & Med Affairs: Accelerated competitive intelligence and evidence dissemination
- With our technology, enterprises unlock the full potential of AI to drive innovation, reduce time-to-insight, and ultimately bring life-changing therapies to market faster and more efficiently.
Opening the deck…
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Best customer profile
Nextnet's ideal customer is a researcher or a scientist within the life science enterprise engaged in research and development. We already have users in over 100 countries and a rapidly growing user base that’s doubling each month. Our current users include biotech startups, pharmaceutical companies, life sciences organizations, medical centers, doctors, clinicians, citizen researchers, and academic labs.
Notable paying customers
- Here is a small sample of the organizations that our users on the Nextnet Free-tier are affiliated with (we are launching our "Starter" subscription plan in July)- Pharma & Life Sciences: GSK Novo Nordisk Eisai Pharma Bio-Rad Labs Thermo Fisher Scientific Ardigen Medical centers: The Broad Institute Memorial Sloan Kettering Cancer Center MD Anderson Cancer Center City of Hope Cancer Center Massachusetts General Hospital Texas Medical Center UAMC Amsterdam Biotech startups: Korro Bio GenEdit Elevate Bio Bloom Science Helix Nano Dewpoint Therapeutics Siren Biotechnology Senti Bio Academic labs - USA: MIT Stanford University Harvard University The Broad Institute UCSF UC Berkeley Georgia Tech UCLA Yale University of Washington Columbia University UC San Diego Purdue University Emory University University of Notre Dame Rutgers University University of Arizona Academic labs – Int’l: Imperial College (London, UK) Queen's University (Belfast, UK) University of Melbourne (Australia) Ben Gurion University (Israel) University of Giessen (Germany) Freie Universität Berlin (Germany) Helmholtz Munich (Germany) Ludwig Maximilian University of Munich (Germany) University of Helsinki (Finland) Radboud University (Netherlands) Seoul National University (S. Korea) University of Chile National Cheng Kung University (Taiwan) Federal University of Minas Gerais (Brazil) National Univ Health System (Singapore) Charité - Univ Medicine Berlin (Germany)
Key milestones
Nextnet has built and shipped the the world’s first AI health knowledge platform built on the world's largest semantic web of health data. Our MVP released in 2024 experienced a 1200% organic user growth Organic growth comes with no dollars spent on advertising or outbound prospecting. Nextnet’s MVP one-month user retention is 30%. Nextnet user registrations from over 100 countries – half from North America and Europe. Other countries include Brazil, Israel, Indonesia, India, Japan, Australia, Taiwan, Singapore, and China. Since our April 2025 launch of the Nextnet flagship product, we are experiencing 2x Month-on-month Organic User Growth Our growth is mirroring early patterns seen in other successful enterprise software companies like Slack and Notion. Average session time is ~20 minutes, with repeat users spending 1-3 hours across multiple sessions. For comparison: WebMD averages ~6 minutes per session with 200M+ MAUs. We have done all of these with a maximum capital raised of $3 Million USD We are launching our "Starter" subscription plan in July and "Pro" and "Pro Plus" subscription tiers in the later part of Q3'2024
Customer case
One customer deployment, shown below.