Causaly vs Iris.ai (2026)
Side-by-side comparison of Causaly vs Iris.ai: pricing, capabilities, integrations, deployment complexity, and ratings. Built from The AI Agent Index's verified listing data. Causaly last verified October 11, 2026. Iris.ai last verified October 13, 2026.
Data sourced from The AI Agent Index
Causaly
by Causaly
Agentic AI research platform for life sciences R&D, grounded in biomedical knowledge graphs. Self-serve plans from $99/mo with a 14-day trial, enterprise via sales.
Iris.ai
by Iris.ai
Enterprise AI platform from Norway that prepares documents and data as knowledge for AI agents, with Axion, Neuralith and RSpace. RSpace individual plan from EUR 292/mo with a trial.
Capabilities
Causaly
Iris.ai
Pros & Limitations
Editorial assessmentCausaly
Pros
- ✓Answers are grounded in Causaly's own biomedical knowledge graphs, with more than 500 million facts in Bio Graph, and every claim links to the highlighted source passage it rests on.
- ✓Documented outcomes at pharmaceutical scale: ProQR reported 5x productivity over PubMed for target identification, and a top-10 global life sciences company cut proposal time by 75% during a disease area transition.
- ✓Open beyond enterprise contracts: self-serve plans from $99 per month with a 14-day trial and no credit card, and enterprise access inside Microsoft 365 Copilot and Teams.
Limitations
- –Built for biomedical and life sciences evidence, so its sources and knowledge graphs add little for research outside that domain.
- –Self-serve plans are single-user with monthly allowances of 400 or 500 credits, the Team plan is not yet available, and enterprise features such as the Enterprise Data Fabric are priced through sales.
- –Customer Content is never used for model training, but customer queries and performance data may be used to develop and improve the software, with a no-training commitment on performance data for Team plan customers.
Iris.ai
Pros
- ✓Covers the path from raw documents to governed knowledge for AI agents, with Axion for data preparation, Neuralith for knowledge graphs and RSpace for research.
- ✓Named customers span manufacturing, agriculture, publishing, research and government, including Mercedes-Benz, ArcelorMittal, Syngenta, USDA and the Max Planck Society.
- ✓Deploys through an API, on-premise or in the cloud, and states ISO 27001 certification and that client data is never used to train general models.
Limitations
- –Axion and Neuralith are sold through a demo request. Only the RSpace Individual Membership has a published price, at EUR 292 per month or EUR 3,500 per year.
- –No public API documentation or MCP server is published, and Axion and Neuralith deployments are scoped with Iris.ai's team rather than set up self-serve.
- –RSpace's cloud import accepts English-language documents only, up to 10,000 documents and 5 GB, and its trial moves to a paid period automatically after 10 days.
Frequently asked questions
How does pricing compare between Causaly vs Iris.ai?
Causaly uses a subscription model, starting at $99 per month. Iris.ai uses a subscription model, starting at EUR 292 per month.
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