Autonomous Agents Enterprise Architecture 4.0 - RAG and GraphRAG - Full Day
AI has permanently transformed the role of Enterprise Architects. Traditional architectures built around data, applications, and integration are no longer enough. Modern intelligent systems rely on retrieval-augmented reasoning (RAG), relationship-driven graph reasoning (GraphRAG), and autonomous AI agents that must operate safely, predictably, and in alignment with business goals.
This full-day immersive workshop introduces the ARCHAI Blueprint, the first EA 4.0 framework that unifies:
– ARCHAI Fabric — enterprise knowledge & reasoning layer powered by RAG and GraphRAG
– ARCHAI Agents — assistive, autonomous, and cooperative agents with guardrails
– ARCHAI View — C4++ modeling for intelligent architectures
– ARCHAI Maturity Model — a 5-level roadmap toward the autonomous enterprise
Through storytelling, live architecture labs, and hands-on modeling, participants will learn how to design safe, scalable, AI-augmented enterprise architectures. You will build an end-to-end architecture for a realistic case study—ArchiMetal, a global manufacturing enterprise modernizing with AI.
By the end, you will not just understand RAG and GraphRAG—you will know how to embed them into production-grade enterprise architecture that is governable, observable, and future-proof.
⸻
KEY TAKEAWAYS
Participants will leave with the ability to:
Architect AI-Driven Knowledge Systems
•Design enterprise-scale RAG and GraphRAG pipelines
•Build knowledge fabrics that unify documents, graphs, embeddings & metadata
•Govern retrieval consistency, drift, safety, lineage & real-time updatesModel Intelligent Systems Using ARCHAI View
•Produce C0 → C3 diagrams (C4++ enhanced for AI)
•Model knowledge flows, agent interactions, guardrails & reasoning boundariesDesign and Govern Enterprise AI Agents
•Define agent roles, decisions, constraints, and safety boundaries
•Create multi-agent workflows across business domains
•Establish guardrail & observability architectureBuild AI-Augmented Business, Data, Application & Technology Architectures
•Extend TOGAF with AI reasoning-layer constructs
•Integrate RAG/GraphRAG into EA artifacts and capability maps
•Architect runtime platforms for inference, retrieval, safety & cost controlCreate an EA 4.0 Roadmap Using the ARCHAI Maturity Model
•Assess enterprise readiness
•Identify transformation milestones across 5 maturity levels
•Build a 12–36 month strategic roadmap for intelligent systems adoption
Welcome & Foundations of EA 4.0
•Why enterprise architecture must evolve for AI
•Overview of the 5 ARCHAI components
•ARCHAI Blueprint
•ARCHAI View
•ARCHAI Fabric
•ARCHAI Agents
•ARCHAI Maturity Model
⸻
Session 1 — Architecture Vision
•The new Enterprise Knowledge & Reasoning Layer
•Why RAG/GraphRAG require architectural foundations
•Intelligent system context modeling (C0/C1)
•Introducing the ArchiMetal case study
⸻
Session 2 — Business Architecture for AI
•Mapping AI-driven capabilities and value streams
•Decision hotspots and agent opportunities
•Business capability redesign
•ARCHAI Maturity Model assessment
⸻
Session 3 — Data Architecture: ARCHAI Fabric
•Designing the knowledge layer (RAG + GraphRAG)
•Vector, graph, ontology, and metadata models
•Governance for retrieval, drift, lineage, and safety
•C2 modeling for the Fabric
⸻
Session 4 — Application Architecture: ARCHAI Agents
•Assistive, autonomous & cooperative agent patterns
•Agent decision boundaries and governance
•Multi-agent workflows & human-in-loop logic
•C2/C3 diagrams for agent flows
⸻
Session 5 — Technology Architecture
•AI & retrieval runtimes
•Guardrail and policy engines
•Observability for reasoning, retrieval, and agent behavior
•Technical standards for EA 4.0 systems
⸻
Session 6 — Integrated Architecture Lab
•Build the full ARCHAI Blueprint for ArchiMetal
•Create C0 → C3 diagrams (ARCHAI View)
•Design Fabric + agent ecosystem
•Map guardrails & governance
•Define the EA 4.0 transformation roadmap
⸻
Session 7 — Governance & Operating Model
•Knowledge governance (Fabric)
•Agent governance (charters, permissions, kill switches)
•Model & retrieval lifecycle governance
•Risk, compliance, auditability
•EA 4.0 operating model for intelligent systems
⸻
Session 8 — Future Trends & Roadmap
•Multi-modal RAG & graph fusion
•Enterprise agent meshes
•Intelligent twins & edge reasoning
•Autonomous governance
•3–5 year ARCHAI roadmap
⸻
Closing & Next Steps
•Recap of frameworks & deliverables
•EA transformation priorities for the next 90 days
•Certification and final Q&A
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of AI & Data Architecture at Salesforce, where he focuses on enterprise AI, agentic systems, cloud-native architecture, distributed systems, data platforms, security, and large-scale transformation.
Over his career, Rohit has designed and led complex enterprise platforms across AWS, Google Cloud, microservices, real-time data, API ecosystems, resilient distributed systems, and AI-enabled architectures. His work increasingly focuses on the challenges enterprises face as software evolves from deterministic services to AI-native and agentic systems—particularly around reliability, governance, evidence, security, observability, cost, and safe autonomy.
Rohit is the author of System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems, published by Apress. The book presents a modern approach to system design covering scalability, distributed systems, AI architecture primitives, security, reliability, economics, agentic systems, and real-world architectures including e-commerce, ride sharing, payments, fraud detection, messaging, video streaming, file storage, and search. (Springer Link)
Book:
Amazon: https://a.co/d/09Zs1twa
Publisher / Springer Nature: https://link.springer.com/book/10.1007/979-8-8688-2782-2
O'Reilly: https://learning.oreilly.com/library/view/system-design-with/9798868827822/
Rohit is also an O’Reilly instructor and a frequent speaker at technology conferences including No Fluff Just Stuff, UberConf, GIDS, and other international events. His talks focus on practical architecture lessons from building and operating complex systems, including AI control planes, trusted agents, inference at scale, evidence-first RAG, AI security, distributed-system failure, and AI-era software architecture.
As a trusted advisor and architecture leader, Rohit works at the intersection of business strategy and deep technical architecture—helping teams translate complex business problems into scalable, resilient, secure, and economically sustainable systems.
Rohit holds an MBA in Corporate Entrepreneurship from Babson College and graduate-level education in Computer Science from Boston University and Harvard University.
Connect with Rohit:
LinkedIn: http://linkedin.com/in/rohit-bhardwaj-cloud
X / Twitter: @rbhardwaj1