Edison Scientific

The agent is the entire product. Kosmos is described as autonomously reading literature, executing analysis code, generating hypotheses, branching investigations, and steering mid run, with independent coverage citing roughly 200 agent rollouts and tens of thousands of lines of executed code within a single campaign lasting up to twelve hours. There is no non AI version of this offering.

This is one of the most autonomous systems in the index, running unattended research campaigns for hours, which raises rather than lowers the oversight burden. Two things earn credit. The output is fully cited, so every claim traces to a source a scientist can check, and the workflow is stated to be fully auditable with analyses, reasoning steps, and decisions traceable. More notable is the founders' own published caution that the system sometimes goes down rabbit holes or chases statistically significant yet scientifically irrelevant findings, and that they often run it multiple times on the same objective. That is an unusually honest limitation disclosure and it tells a buyer exactly what the review obligation is.

The architecture is described in public technical writing rather than asserted: a structured world model coordinates agents and maintains coherence across hundreds of steps, with a published technical report and engineering write ups on how the platform was built. An open source implementation is reported to exist allowing self hosting across multiple model providers, which is the strongest form of transparency available and rare anywhere in this index. Underlying foundation model providers are not named on the commercial platform.

Evidence is research productivity rather than clinical outcome, which is the right measure for this product. The company reports collaborators finding a single 20 cycle run equivalent to roughly six months of their own research time, and a named partner describes 292 independent analysis trajectories in 24 hours surfacing insights their team had missed. Specific scientific findings have been described in the Alzheimer's research literature. What is missing is independent controlled evaluation of output quality, and the vendor's own caveat about irrelevant findings means throughput claims should not be read as accuracy claims.

No PHI surface in the core product, which operates on research data and literature. Where partners feed translational and clinical data into the platform, the governing controls are the enterprise deployment terms rather than a published PHI framework. Data is stated to be encrypted in transit and at rest with account deletion rights under the privacy policy.

No HIPAA or BAA commitment located. The buyer is a biopharma R&D organization rather than a covered entity, so this axis is largely inapplicable, but any deployment touching identifiable clinical trial data would need it established contractually.

SOC 2 Type II compliance is stated on the main site, and the company describes enterprise deployment on SOC 2 compliant infrastructure with fully auditable workflows. The engineering write up is candid that supporting agents executing arbitrary code is a substantial security challenge in a regulated environment, which is the correct thing for a buyer to be thinking about. No trust center with downloadable artifacts was located.

No FDA pathway applies. This is a research acceleration platform operating upstream of any regulated claim, and it makes no diagnostic or treatment recommendation.

No formal governance framework is published, but the substance that governance is meant to produce partially exists: the founders publicly document failure modes, the outputs are cited and auditable, and the technical report allows external scrutiny. Credit is limited because none of this is a stated governance program with monitoring commitments, and no evaluation of systematic bias in hypothesis generation was located.

No EHR surface. Integration is with internal research tools and datasets on the enterprise tier, and collaboration happens through Slack, Teams, and email rather than clinical systems.

The strongest disclosure on this axis among the vendors added in this batch. The company states enterprise deployment happens in the customer's own environment so the customer retains full governance, and explicitly that model training on customer data is retained only as it serves the customer. For biopharma organizations whose proprietary experimental data is the asset at risk, an in environment deployment with an affirmative training data position is the material term, and it is stated plainly rather than left to negotiation.

Published pricing in a category where essentially nobody publishes. Tiers are listed with credit allocations, a free tier with 10 expiring credits per month, a paid tier with 650 expiring credits per month including Kosmos access and additional non expiring credits purchasable at one dollar per credit, and a separately quoted enterprise tier. Independent reporting notes academic users received the first six Kosmos runs free at roughly 200 dollars per run thereafter. A buyer can estimate spend before contacting sales, which is the point of this axis.

Domain coverage is genuinely broad, spanning neuroscience, metabolomics, genetics, and materials science, with the platform positioned across biology, chemistry, and physics. The healthcare relevant surface is narrower than that range implies: the buyer is a pharma or biotech R&D organization, with the disclosed enterprise partnership focused on target discovery, validation, and translational biology. This is not a provider facing product and should not be evaluated as one.