Causaly Introduces Agentic Research AI Platform For Life Sciences R&D
Causaly has announced Causaly Agentic Research, a new AI platform designed to support life sciences R&D with domain-specific “agentic” AI. The system aims to outperform literature review tools and general-purpose AI by combining internal and external biomedical data with the industry-specific agentic AI into a single evidence layer.
At the core of the platform is a Data Fabric that integrates scientific literature, competitor intelligence, and private research. Building on this foundation are several specialized components:
- Bio Graph – maps cause–effect relationships in biomedical data, powering the Bio Graph Agent
- Pipeline Graph – organizes targets, modalities, and indications to guide the Pipeline Graph Agent
- Scientific Information Retrieval System (SIRS) – combines advanced search and reasoning to surface precise, context-rich insights
The platform structure is visually illustrated below:
Together, these systems integrate more than 500 million curated data points with contextual evidence. The company positions this as a response to longstanding bottlenecks in drug discovery and development: siloed data, manual analysis, and the challenge of keeping pace with rapidly expanding biomedical information. By automating multi-step workflows—ranging from hypothesis generation to structured analysis—and continuously scanning the scientific landscape, the agents aim to reduce bias, improve decision-making, and accelerate time-to-discovery while maintaining traceability for regulatory purposes.
Causaly Agentic Research will be available in October 2025 with an initial set of agents and a conversational interface. Additional specialized agents are expected by the end of the year.
Link to the platform: https://www.causaly.com/products/agentic-research
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Topic: AI in Bio
