Connected Papers vs Iris.ai
Compare research AI Tools
Connected Papers
Visual literature maps that reveal related work around a seed paper, helping researchers explore fields, spot clusters, and find influential prior art quickly.
Iris.ai
Enterprise retrieval and evaluation platform for secure agentic AI over private corpora with workflows for ingestion testing and governance.
Feature Tags Comparison
Only in Connected Papers
Shared
Only in Iris.ai
Key Features
Connected Papers
- • Graph of related papers via co-citation analysis
- • Cluster views to identify schools of thought and methods
- • Filters for date influence and distance from seed
- • Snapshots and exports for sharing reading lists
- • Links out to publisher pages and repositories
- • Free tier plus Academic and Business plans
Iris.ai
- • Governed Ingestion: Connect wikis drives and repos then normalize content with metadata access rules and retention policies for compliance
- • Evaluation Workflows: Run automatic metrics and human rubrics to measure accuracy hallucination rate and coverage before launch
- • Guardrails and Policies: Define prompts filters and safety limits that block sensitive data flow and unsafe responses in production
- • Observability and Drift: Track quality usage and model costs then alert owners when performance moves outside accepted ranges
- • Integrations: Use existing vector stores model providers and identity controls so deployments align with current architecture
- • Red Teaming: Exercise prompts tools and environments to uncover jailbreaks and leakage risks before go live
Use Cases
Connected Papers
- → Map a field around a seminal work in minutes
- → Assemble a syllabus or lab reading plan by cluster
- → Validate novelty and check for near-duplicate ideas
- → Find bridges between subfields for new directions
- → Identify review papers to onboard collaborators
- → Export candidates to your reference manager
Iris.ai
- → Stand up secure knowledge assistants for employees that search approved sources with clear citations
- → Reduce support handle time by routing assistants to articles with evaluation backed accuracy and policy bounds
- → Enable research teams to explore large archives and synthesize findings with traceable sources for compliance
- → Run pilots that compare prompts models and retrieval settings to pick the highest quality approach
- → Prepare audit evidence with documented controls and results to satisfy internal and external requirements
- → Connect identity and permissions so assistants respect document level access across departments
Perfect For
Connected Papers
graduate students PIs applied scientists startup R&D and analysts who need fast field maps and curated reading paths
Iris.ai
enterprise knowledge leaders compliance teams information security and platform engineers who need measurable safe retrieval over private data
Capabilities
Connected Papers
Iris.ai
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