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Causaly Introduces First Agentic AI Platform Built for Life Sciences Research and Development

by Syed Hamza Sohail 09/16/2025 Leave a Comment

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What You Should Know:

– Causaly today announced Causaly Agentic Research, an agentic AI platform designed specifically for life sciences research and development.

– Built to deliver transparency and scientific rigor, the platform’s specialized AI agents access, analyze, and synthesize internal and external biomedical knowledge and competitive intelligence—so teams can automate complex workflows, uncover novel insights, and move from hypothesis to decision faster and with greater confidence. 

A scientific AI built for how researchers actually work

Extending Causaly Deep Research, the new offering introduces a conversational interface that lets scientists partner directly with AI research agents. Unlike general-purpose tools or static literature review software, Causaly’s agents are trained for life sciences R&D and securely unify internal and external data into a single source of truth. They execute multi-step research tasks—from hypothesis generation and testing to structured, transparent outputs—always grounded in traceable evidence. 

“Agentic AI fundamentally changes how life sciences conducts research,” said Yiannis Kiachopoulos, co-founder and CEO of Causaly. “Causaly Agentic Research emulates the scientific process—analyzing data, mapping biological relationships, and reasoning through problems—so scientists can reduce manual work, de-risk decisions, and focus on higher-value science.” 

Solving the bottlenecks slowing discovery

R&D organizations grapple with vast, rapidly expanding biomedical information. Manual, siloed processes lengthen cycles, hide critical signals, and introduce bias. By combining extensive biomedical sources with competitive intelligence and proprietary datasets in one intelligent interface that fits existing workflows, Causaly helps teams break down silos, boost productivity, and accelerate ideas to market. 

What the agents do

  • Advance complex analyses and provide answers that propel research forward
  • Verify quality and accuracy, compressing time-to-discovery
  • Continuously scan the landscape to surface critical signals and emerging evidence in real time
  • Deliver fully traceable insights to support confident, evidence-backed decisions and regulatory rigor
  • Connect across systems and data—including public apps and other AI agents—to unify discovery workflows 
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