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DeepKin.ai
BioTech OpenEvidence for Investors
About us
DeepKin automates the science-heavy side of biopharma equity research. Built on Yale-originated DeepAgent IP and research from Yale’s Clinical NLP Lab, the platform uses multi-agent reasoning framework over curated biomedical, clinical, regulatory, and market data to turn drug-development evidence into faster, broader, and more verifiable investment insight.
Our Solution
Retrieve
Scientific papers, clinical trial records, FDA documents, Labels, SEC company filings, and market context.
Outputs are organized into comparable reports, pipeline views, and decision-ready summaries.
Structure
Reasoning
Specialist agents compare mechanisms, assess precedents, evaluate design, and reconcile conflicting signals.
Evidence links and source-level traceability support review instead of black-box answers.
Verify
Drug Asset Research Across the Lifecycle
Each stage requires a different schema, evidence set, and analytical focus — all connected through a unified competitive landscape engine.
Our Expertise
Evidence-based Intelligence
Turns complex source data into actionable investment insights
Multi-agent architecture
Self-adaptive multi-agent framework with long-term memory and risk control
Biomedical Signal Mining
Extracts high-value patterns from scientific literature, trials, and regulatory data
Collaborative Research Network
Advance and validate agentic science for finance together with academia and industry
News
When Agents Trade: Live Multi-Market Trading Benchmark for LLM Agents
FINCON: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks
with LLM-based Agent
Our Partners
The Fin AI
Get in Touch
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