What does Causaly do?

Causaly is an AI platform for life sciences research and development that uses agentic AI, precision knowledge graphs, and workflow automation to help scientists accelerate drug discovery. It includes an AI copilot for asking scientific questions, access to a biomedical knowledge graph covering 500 million relationships, and tools for target identification, biomarker discovery, and disease research.

Who is Causaly best for?

Causaly is designed for biomedical scientists, bioinformaticians, and pharmaceutical R&D teams who need to rapidly analyze biomedical data, identify drug targets, discover biomarkers, and make evidence-backed research decisions.

Does Causaly have a plan for teams or businesses?

Yes, Causaly offers products designed for teams and organizations, including Agentic Research for science-grade AI in R&D, Discover for scaling research across your workforce, and Bio Graph API for integrating the knowledge graph into your systems.

Does Causaly offer an API or integrations?

Yes, Causaly offers a Bio Graph API that allows developers to query the biomedical knowledge graph and integrate it into applications and workflows. The API includes simple token authentication, pre-made templates, and R and Python libraries. Causaly also integrates with Datadog for automated root cause analysis.

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Causaly

Healthcare & Wellness+1Research & Analysis

An agentic AI platform that helps pharmaceutical and biotech R&D teams find, visualize, and verify biomedical evidence using knowledge graphs and automated workflows.

Available Via:WebAPI

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Causaly is a web-based agentic AI platform for life sciences enterprises that supports drug discovery and development teams with evidence-backed research, analysis, and workflow automation.

Key capabilities include:

Agentic Research for multi-step R&D tasks, where domain-specialized agents plan, search, reason, and produce structured outputs backed by traceable evidence.
Precision biomedical knowledge graphs (including Bio Graph) to retrieve and interpret relationships in biology, helping teams visualize pathways, mechanisms, targets, and biomarkers.
Scientific information retrieval (Scientific RAG / SIRS) that ranks for relevance, returns cited results, and handles no-answer scenarios to reduce hallucination risk.
Enterprise data integration via an Enterprise Data Fabric, combining internal data, external biomedical sources, and pipeline-level competitive intelligence (Pipeline Graph) in a single workspace.

Pricing: Not disclosed publicly.

What makes it notable: Unlike general-purpose chat tools, it is built specifically for high-stakes life sciences R&D, emphasizing traceability, quality verification, and governed agent orchestration to support decision-making where scientific rigor and regulatory readiness matter.

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