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.

AI/LLM Ongoing
Rai — Agentic AI for Identity

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