The AI-Native Infrastructure for Clinical Research
Explainable automation that strengthens clinical research operations, produces regulator-ready datasets, and empowers hospitals to run more trials with confidence.
The Hidden Drag on Discovery
Manual Workflows
Eligibility, re-screening, compliance, and adverse event logging still drain staff time.
Coordinator Bottlenecks
Departments hit ceilings and many IITs never launch despite $5–15M budgets in oncology alone.
Sponsor Delays
Enrollment lags and site data varies, costing $1–6M per day in blockbuster trials.
Opaque Outputs
Despite billions invested, trial datasets remain inconsistent and difficult to reuse.
Damaros Turbocharges Your Workflow
Damaros is built on lightweight, explainable language models. The current prototype captures secure workflows, audit logs, and structured trial data. From here, lightweight agents will automate manual steps inside the hospital firewall, compounding into long-term institutional assets.The Dual Engine Damaros Platform
LUNA
LUNA begins by turning oversight into structure: trial runs and protocol amendments are captured in an auditable ledger. Our roadmap makes every future agent decision explainable and regulator-ready.
NECTOR
NECTOR begins with structured exhaust: trial data captured in a durable, hospital-owned format. Over time, this foundation compounds into evidence streams that accelerate trials and strengthen trust.
The Spine Across Silos
Hospitals
Hospitals launch more IITs with the same coordinators, easing bottlenecks while capturing overhead revenue and academic visibility without adding staff.
Industry
Sponsors and CROs gain speed and consistency across hospitals, reducing costly delays and delivering cleaner, regulator-ready enrollment data.
Regulators
Regulators and IRBs gain clear, auditable workflows with compliance built in, lowering review friction and reinforcing trust in every trial dataset.

