Causaly combines AI agents with your scientific methods, evidence standards and review criteria to produce work that scientists can inspect, challenge and use.
Request a demoSupporting scientific teams across life sciences.
Start with established scientific workflows, developed with customers and supported by Causaly’s in-house scientists. Use the methods already built into the platform, or work with us to adapt the evidence, criteria and deliverable to your organization.
Causaly brings together human genetics, mechanism, safety and competitive evidence in an established assessment. Apply the existing method, or adapt the evidence hierarchy and prioritization criteria to your team.
Analyze data, interpret the science, work through a whole list and create the finished deliverable. One assignment can combine all four.
Explain a signal in its biological context. Test competing explanations and make assumptions, contradictory evidence and uncertainty explicit.
Check the inputs, apply the method and compute the result. Keep the code, parameters and numerical outputs available for review.
Apply an operation across an entire list. Track each item, retain progress and distinguish completed searches, no matches and failures.
Turn scientific findings into a polished report or presentation, preserving meaning, figures and the evidence behind each claim.
Causaly connects scientific data, knowledge graphs and AI agents so your team can explore biology, assess hypotheses and apply its methods through repeatable workflows. Follow the evidence and reasoning behind the work, with outputs ready for expert review.
Coordinate scientific agents to apply your methods, check the evidence and deliver work for expert review.
Learn more ↗Connect biological relationships with research programs and development activity to assess evidence in context. Compare targets, modalities and development stages to identify crowded areas and assess differentiation before committing resources.
Learn more ↗Find relevant evidence through semantic and graph-based retrieval, with source passages that scientists can inspect.
Learn more ↗Bring literature, scientific data and internal knowledge together as a foundation for scientific work.
Learn more ↗Build on Causaly’s literature, scientific data, knowledge graphs and scientific harness. Access scientific capabilities through MCP, A2A and APIs, extend established workflows, or codify your own with our scientific team.
Invoke Causaly’s scientific capabilities from your architecture.
Extend existing methods or encode a specialized process with our scientists.
Combine Causaly with the platforms and computational tools your teams use.
▤ Scientists can also work directly in Causaly’s interface.
Explore an established workflow, adapt it to your standards, or build a new scientific process with Causaly.
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