Agentic Research

Agentic Research by Causaly is an autonomous AI research platform purpose-built for life sciences R&D teams. It combines a conversational interface, a comprehensive biomedical data fabric, and autonomous AI research agents into a single unified platform, enabling scientists to accelerate discovery, reduce risk, and make faster, more defensible decisions across the entire drug development pipeline.

Designed to address the core challenges of siloed teams, manual workflows, and fragmented tooling, Agentic Research automates up to 80% of R&D workflows and applies domain-specific reasoning to surface hidden insights with transparency and precision. The platform achieves 93% accuracy on biomedical claims through tight hallucination controls and 88% precision on expert biomedical questions in the LitQA2 benchmark, reading up to 400 documents per minute — a task that would otherwise take a week to complete manually.

Core Platform Capabilities

• Decision making through data: Every conclusion is reached with transparent logic, full disclosure of assumptions and limitations, and every claim linked directly to supporting evidence.
• Faster evidence generation: Agents automate planning, search, and synthesis; a simple conversational interface enables exploration of complex questions; and tailored guidance helps uncover hidden insights.
• Scientific rigor at scale: AI agents are designed to replicate the scientific process, with comprehensive coverage across diverse data sources, integrated data, and built-in hallucination guardrails for safer, more reliable outputs.

Supporting the Full R&D Lifecycle

• Target identification and prioritization: Workflow automations built for target assessment save R&D scientists thousands of hours annually and unlock new revenue potential.
• Biomarker discovery: Removes human bias from the discovery process and leverages hundreds of millions of public and proprietary data points to reduce research workflows from months to minutes.
• Drug repurposing: Identifies and validates new uses for existing drugs by uncovering hidden drug–target–disease connections and prioritizing repurposing opportunities.

Underlying Data and Intelligence Infrastructure

• Data Fabric: Unifies literature, competitor intelligence, and private research into one governed evidence layer.
• Bio Graph: Reveals biomedical cause–effect relationships, powering the Bio Graph Agent.
• Pipeline Graph: Maps targets, modalities, and indication landscapes to drive the Pipeline Graph Agent.
• Scientific Information Retrieval System (SIRS): Combines advanced search and reasoning to surface precise, context-rich insights.

Together, these components draw on more than 500 million curated data points, enabling R&D teams to move confidently from pathway analysis to pipeline decisions. Causaly also offers professional services led by PhD scientists and change management experts, providing end-to-end support from strategic alignment and deployment planning through to ongoing research enablement. The platform is enterprise-ready, integrating seamlessly with existing systems and agent platforms, enforcing security policies, managing access controls, tracking activity for accountability, and adhering to data governance and compliance frameworks.