Consensus
AI research engine that answers questions with evidence from peer-reviewed studies, showing citations, study design, and summaries you can verify quickly.
BabyAGI
Experimental open source project that explores autonomous task planning and self improving agents often used for demos education and research rather than production systems.
Feature Tags Comparison
Only in Consensus
Shared
Only in BabyAGI
Key Features
Consensus
- • Evidence-based answers with citations and study design
- • Pro searches that read full texts for deeper synthesis
- • Filters by topic outcome and study characteristics
- • Snapshots and summaries you can export to notes
- • Account tiers for individuals academics and teams
- • Interface designed to keep verification one click away
BabyAGI
- • Core Loop: Generate a task list execute a task evaluate outcome and create new tasks
- • Minimal Codebase: Small readable project
- • Self Improvement: Emphasis on feedback and recursion
- • Community Ecosystem: Many forks and tutorials
- • Extensible Concepts: Combine with retrieval tools and memory
- • Educational Value: Shows agent pitfalls
Use Cases
Consensus
- → Orient a lit review with quick evidence snapshots
- → Brief executives with short answers plus citations
- → Check whether claims are supported by controlled trials
- → Find meta-analyses and systematic reviews fast
- → Compare outcomes across interventions or protocols
- → Export concise notes for papers worth a deep read
BabyAGI
- → Classroom Labs: Demonstrate planning reflection iteration
- → Research Prototypes: Test memory strategies and reflection patterns
- → Internal Workshops: Teach teams how agent loops work
- → Content Experiments: Generate outlines steps critiques
- → Data Tasks: Toy agents that fetch transform summarize
- → Developer Education: Teach stopping criteria and retries
Perfect For
Consensus
students clinicians researchers policy analysts product managers and writers who need fast evidence-first answers with links to papers
BabyAGI
Students, researchers, tinkerers, and engineering teams who want to learn autonomous agent patterns in a small codebase before adopting governed frameworks for production use
Capabilities
Consensus
BabyAGI
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