Causaly announced the launch of Agentic Research, a groundbreaking platform of multi-autonomous AI research agents designed specifically for life sciences research and development (R&D). This innovation sets a new standard for scientific decision-making, delivering faster, more confident outcomes, deeply grounded in evidence.
Agentic Research redefines how scientists interact with knowledge. It enables AI agents to plan, research, and synthesize biomedical evidence while explaining every step of their reasoning. The platform is purpose-built to close the gap between search tools and research workflows, addressing the complexities, risks, and information overload that life sciences R&D faces today.
Yiannis Kiachopoulos, in announcing the launch, stated, “Overcoming the Toxicity Hurdle in Clinical Development.” He emphasized the urgent need for innovation in scientific decision-making given that choices in target selection, biomarker validation, and trial planning determine whether a therapy succeeds or assets stall in the pipeline.
Key Features of Agentic Research
Causaly has built three foundational capabilities into Agentic Research:
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Scientific retrieval – Domain-specific retrieval using ontologies and normalized entities to find the most relevant scientific literature, extract facts, and rank results by scientific signal.
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Data fabric with two graphs – The Bio Graph models cause-effect relationships; the Pipeline Graph maps targets, modalities, and indications; both anchored in a proprietary biomedical fabric.
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Built for scientists – Designed for transparency and ease of use: every claim links to sources in an evidence matrix; logs capture assumptions, limitations, and methods; multi-turn workflows support transitions from search to Deep Research which teams can review, revise, and reproduce.
These capabilities position Agentic Research as more than a generic AI tool. It aligns with how scientific research and platform work in practice.
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Impact for R&D Leaders and Technology Organizations
The platform offers several benefits to R&D leaders, including compression of research timelines (automating up to 80% of scientific workflows), improved success rates via comprehensive evidence integration and advanced reasoning, increased capacity with existing scientific resources, and enabling earlier, more confident decisions that protect asset value and speed development.
For CIOs and tech leaders, Agentic Research delivers seamless integration with legacy systems and modern infrastructure; orchestration of AI agents across internal and third-party systems (including OpenAI, Google Agentspace, AWS Bedrock); governance features including policy enforcement, hallucination guardrails, and audit logs; and a unified interface that drives adoption across scientific teams without creating “shadow AI.”
Comprehensive Support Across R&D Use Cases
Agentic Research supports the entire R&D continuum, from discovery through clinical development. Specific use cases include:
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Target identification and prioritization
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Disease mechanism mapping
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Biomarker discovery and modality comparison
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Hypothesis testing and synthesis
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Trial planning and clinical decision support
Irrespective of whether teams are involved in discovery, translational research, or clinical development, Agentic Research equips them to move faster and think more deeply without sacrificing rigor.
“Agentic Research is a research partner that is transparent, rigorous, and built for science,” the company stated. It underscores Causaly’s view that AI should not replace scientists but empower them with agents that reason, orchestrate, and deliver evidence with confidence.
