Agentic RAG in Production: Orchestration, Evaluation & ROI
Most RAG pilots stall after the demo stage — they hallucinate, fail under orchestration, or can’t prove measurable ROI.
This session introduces Agentic RAG: retrieval that’s decided, evaluated, and improved by agents inside enterprise workflows.
You’ll learn how to combine:
- Salesforce Agentforce for agentic orchestration in sales, service, and checkout flows.
- Data Cloud as the factual grounding layer with Customer 360 and predictive signals.
- LangGraph orchestration patterns for multi-agent reasoning, reflection, and escalation.
- Evaluation frameworks (RAG Triad, TruLens, Ragas) for provable accuracy, fairness, and ROI.
We’ll end with a live scenario — the Smart Checkout Helper — that grounds itself in customer data, self-corrects, and quantifies business lift.
Problems Solved
- RAG prototypes hallucinate or fail under enterprise constraints
- Lack of orchestration between retrieval, reflection, and agent decisions
- Inability to measure accuracy, groundedness, or ROI
- Poor alignment between AI output and business outcomes
- Missing governance for privacy, bias, and auditability
Why Now
- RAG must evolve from prototypes to governed, production-grade systems
- Enterprises demand traceable, measurable, and self-improving AI
- Platforms like Salesforce Agentforce and Data Cloud now enable full-stack orchestration and grounding
- LangGraph and similar frameworks make multi-agent reasoning practical
Core Concepts
- Data Cloud Grounding: Use Customer 360 and predictive scores to anchor context.
- Agentforce Orchestration: Embed agentic flows that choose when and how to retrieve or act.
- LangGraph Patterns: Supervisor, Pub/Sub, and Router designs for dynamic control.
- Agentic RAG Patterns: retrieve/skip, reflect/re-query, and multi-hop retrieval loops.
- Evaluation Tooling: RAG Triad (context, groundedness, relevance), TruLens, and Ragas for continuous validation.
- Governance Framework: Privacy, bias mitigation, and fallback mechanisms.
- ROI Focus: Conversion lift, call deflection, and AHT reduction as measurable outcomes.
Agenda
Introduction: From RAG Demos to Enterprise Systems
Why most RAG initiatives fail beyond proof-of-concept.
The shift from static retrieval to agentic orchestration and measurable grounding.
Pattern 1: Grounding in Salesforce Data Cloud
How Data Cloud provides the factual substrate: traits, segments, and predictive scores.
Designing retrievers that query governed, unified customer data.
Pattern 2: Agentic Execution in Salesforce Agentforce
How agents in Agentforce can decide when to retrieve, re-evaluate, or escalate.
Sales, service, and checkout scenarios — driven by decision orchestration.
Pattern 3: Orchestration with LangGraph
Building reasoning loops using Supervisor, Pub/Sub, and Router nodes.
Designing agent workflows with multi-hop and reflection capabilities.
Pattern 4: Evaluation Frameworks & Tooling
RAG Triad metrics: context precision, groundedness, and relevance.
Hands-on tooling: TruLens, Ragas, and observability dashboards for factuality and fairness.
Integrating continuous evaluation into CI/CD for AI pipelines.
Pattern 5: Governance & Responsible AI
Embedding privacy, bias, and audit controls into the orchestration layer.
Designing fallback modes and traceability for compliant AI operations.
Pattern 6: Measuring ROI & Business Impact
Mapping RAG metrics to business KPIs:
- Service: Deflection rate, AHT reduction
- Sales: Conversion lift, deal velocity
- Marketing: Engagement uplift, cost per interaction
How to communicate ROI to leadership.
Demo: Smart Checkout Helper A self-correcting, grounded AI agent combining: - Data Cloud grounding
- Agentforce orchestration
- LangGraph reasoning
- RAG Triad evaluation
Live flow from retrieval → reasoning → measurement.
Wrap-Up & Discussion Key design principles for moving from demo to deployment. Checklist for Agentic RAG production readiness and ROI measurement.
Key Framework References
- Salesforce Agentforce: Multi-agent orchestration and decision workflows
- Salesforce Data Cloud: Unified traits, grounding layer, and predictive signals
- LangGraph: Graph-based orchestration patterns for reasoning and reflection
- RAG Triad, TruLens, Ragas: Evaluation and quality measurement frameworks
- NIST AI RMF / ISO 42001: Governance and explainability alignment
Takeaways
- End-to-end Agentic RAG Architecture Blueprint
- Evaluation Playbook for context, groundedness, and relevance
- ROI Measurement Framework linking AI metrics to business outcomes
- Governance Checklist for privacy, fairness, and resilience
- Ready-to-adapt Smart Checkout Helper reference design
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.