What is Kosmos?
A long-running AI scientist for literature review and hypotheses.
Who is Kosmos best for?
Kosmos is best for biopharma and academic research teams that want an AI to review the literature, analyse their data and test hypotheses.
Biopharma R&D teams
It covers work from target identification through clinical development and regulatory filing, and can run inside the company's own environment.
Large literature reviews
A single run can read 1,500 papers, and it can draw on licensed Nature portfolio journals as it works.
Hypotheses and data analysis
It analyses data, generates and branches hypotheses and runs scientific workflows on its own, while researchers can steer it mid-run.
Teams with their own lab data
It connects to lab notebooks, assay and biomarker data and cloud storage, so its reasoning builds on the organisation's past experiments.
How much does Kosmos cost?
Kosmos does not publish prices: Edison Scientific sells it to research teams through a demo request, and access to the latest version is by application.
Edison Scientific has no pricing page: teams book a demo, and researchers apply for access to the current Kosmos. The maker has retired its earlier founding subscriptions and lists no current plans or prices. Plans and current prices are on edisonscientific.com.
How do readers rate Kosmos?
No one has rated Kosmos yet. Be the first.
Sign in to rate. One rating per account.
Questions about Kosmos
What is Kosmos?
A long-running AI scientist for literature review and hypotheses.
Who is Kosmos for?
Kosmos is best for biopharma and academic research teams that want an AI to review the literature, analyse their data and test hypotheses.
Is Kosmos free?
No. Kosmos is a paid tool.
Where can I try Kosmos?
On its official website, edisonscientific.com.
Can Kosmos run inside our own environment?
Yes. Edison Scientific offers Kosmos as an on-premises deployment in the customer's environment, says it is SOC 2 Type II compliant, and pairs enterprise customers with its own scientists, who work alongside their team and build custom world models on their data.







