Nextnet

Nextnet is a life sciences AI knowledge platform designed to support researchers across academia, biotech, and pharmaceutical organisations. The platform combines AI-powered research assistants with a connected knowledge search engine, all underpinned by a semantic web that unifies biomedical data from sources including PubMed, ChEMBL, Google Scholar, and Ensembl, among others.

Nextnet serves a range of user types, from individual researchers and academic teams to biotech startups and large pharmaceutical enterprises. The platform is available on Free and Starter subscription plans, with an enterprise tier in development for organisations requiring additional security and compliance controls.

Nextnet Copilot

• An AI research assistant for life sciences, functioning similarly to tools such as ChatGPT or Perplexity but with answers grounded in verified scientific sources drawn from Nextnet's semantic web.
• Delivers evidence-backed responses designed to reduce hallucinations by sourcing answers from confirmed biomedical literature and data.
• Connects answers directly to excerpts from relevant papers, allowing researchers to navigate source material through a built-in Reader.
• Filters results to surface only the most relevant science, reducing time spent searching across multiple tools.
• Supports curation workflows, enabling researchers to collect relevant science and pass it to Nextnet Explorer for deeper analysis.

Nextnet Explorer

• Described as a Connected Search Engine for life sciences, Explorer visualises biomedical data as interactive brainstorming maps.
• Reveals relationships across literature, genes, drugs, targets, pathways, diseases, institutions, and authors.
• Supports both a map view for discovering unexpected connections and a list view for reviewing detailed properties of individual biomedical entities.
• Includes collaboration features allowing users to share discoveries, comment, and work across disciplines and teams.
• Future planned additions include coverage of patents, clinical trials, and grants.

Nextnet Semantic Web

• Described as the world's largest semantic web of life sciences knowledge, the underlying data layer transforms fragmented biomedical databases into a unified knowledge base.
• Uses an ontology to model semantic concepts and relationships linking literature, genes, drugs, targets, pathways, and additional biomedical entities.
• Integrates data from ChEMBL, Google Scholar, PubMed, Ensembl, and other sources into a single searchable platform.

Platform Capabilities by Team Type

• Individuals: Supports starting research projects quickly, pinpointing relevant papers in minutes, and sharing with guests.
• Biotech Startups: Provides a data platform without requiring a dedicated data team, supports co-development with academic labs and pharma partners, and offers institutional memory and knowledge management.
• Academia: Equips students and doctoral candidates with AI-powered research tools at accessible price points, and supports partnerships with biotech and pharma organisations.
• Pharma and Enterprise (forthcoming): Planned features include greater organisational privacy controls, durable institutional memory, single sign-on (SSO) and two-factor authentication (2FA), bring-your-own data integration, and security compliance for SOC 2 and ISO 27001 standards.

Nextnet positions itself as a unified research hub intended to reduce the need for researchers to switch between multiple tools, consolidating literature search, data visualisation, AI-assisted querying, and team collaboration within a single platform.