Rai — Agentic AI for Identity
Production-oriented agentic AI service for identity, assurance, and admin workflows. Combines domain-specialist agents, RBAC-scoped tools, retrieval-augmented generation, and fail-closed safety gates — including step-up authentication, citation enforcement, and versioned prompts — to augment identity platforms through HTTP adapters.
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Technology Stack
Python
FastAPI
LangChain
FAISS
RAG
OpenAI
Groq
Kubernetes
Helm
OAuth2
MFA
Eval Harnesses
CI/CD
Key Results
Domain-specialist agents with tool-calling and structured action flows
Architecture
Fail-closed gates, step-up auth, citation enforcement
Safety
RAG pipeline with versioned prompts
Retrieval
Golden eval suites with CI-gated releases
Quality
HTTP adapters for identity and admin platforms
Integration
Pre-commercial (private)
Release Stage
Challenges & Solutions
- Grounding agent responses in identity context without treating user content as system instructions
- Enforcing fail-closed assurance: step-up MFA, tenant isolation, and audit trails on tool execution
- Designing RBAC-scoped tools so agents can only act within the caller's authorized identity scope
- Building eval harnesses and CI release gates for LLM behavior in security-critical workflows
- Integrating with identity gateways via trusted headers and same-origin proxy patterns
- Versioning prompts and measuring regression across golden eval cases before production release
Project Stats
N/A
Team
Ongoing
Duration