Iris.ai vs Research Rabbit
Compare research AI Tools
20% Similar — based on 3 shared tags
Enterprise retrieval and evaluation platform for secure agentic AI over private corpora with workflows for ingestion testing and governance.
ResearchRabbit is an AI assisted literature discovery tool that helps you find related papers and authors, build citation maps, and track research trends with alerts, offering a free plan with unlimited searches and one project plus an optional RR+ subscription.
Feature Tags Comparison
Key Features
- 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
- Citation maps: Visualize connections between papers so you can see clusters and influential work rather than reading in isolation
- Collections and projects: Save papers into collections and organize them as projects to keep a literature review structured
- Author exploration: Follow authors related to your collection to discover their other papers and see how networks evolve
- Research alerts: Get alerts tied to your collections so new relevant papers are suggested without repeating manual searches
- Seed based discovery: Start from up to 50 input papers in the free plan and expand outward using related work suggestions
- Large coverage claim: The pricing page states searches span 280 plus million articles which helps broad discovery across fields
Use Cases
- 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
- Literature review start: Add a few seed papers then use citation maps to find foundational work and recent branches quickly
- Thesis topic discovery: Explore clusters around an idea and identify gaps where fewer papers connect or methods are missing
- Author tracking: Follow key authors from your collection to discover their latest publications and related collaborators
- Staying current: Use collection alerts to surface new relevant papers so you keep up with fast moving fields efficiently
- Cross discipline scan: Start with one paper then expand to adjacent domains to find methods you can transfer to your project
- Reading list curation: Build a structured reading list inside a project so you can prioritize what to read and why it matters
Perfect For
enterprise knowledge leaders compliance teams information security and platform engineers who need measurable safe retrieval over private data
researchers, graduate students, librarians, lab managers, systematic review teams, R and D analysts, academics who need citation maps alerts and structured collections
Capabilities
Governed sources Professional
Quality and safety Professional
Policies and guardrails Intermediate
Drift and reporting Intermediate
Citation map views Professional
Collections and projects Intermediate
Alerts and tracking Intermediate
Seed based discovery Professional
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