Iris.ai
Enterprise retrieval and evaluation platform for secure agentic AI over private corpora with workflows for ingestion testing and governance.
Pricing By quote
Category research
Difficulty Beginner
Type Web App
Status Active
B
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.
Pricing Free
Category research
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Iris.ai
retrievalenterprisegovernanceevaluationsecurity
Shared
None
Only in BabyAGI
agentsautonomousopen-sourceexperimentseducation
Key Features
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
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
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
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
Iris.ai
enterprise knowledge leaders compliance teams information security and platform engineers who need measurable safe retrieval over private data
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
Iris.ai
Governed sources Professional
Quality and safety Professional
Policies and guardrails Intermediate
Drift and reporting Intermediate
BabyAGI
Task Queue Basic
Self Improvement Basic
Tools and Memory Basic
Human Oversight Basic
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