RAG Readiness
Assessment
Before you build a RAG system, make sure the foundation is right. Mobiloitte’s RAG Readiness Assessment helps you evaluate whether your knowledge sources, retrieval strategy, deployment model, and governance controls are ready for a reliable, citation-backed enterprise RAG rollout.
A Practical
First Step
Evaluating whether documents and repositories can support grounded answers.
Determining if you need semantic, keyword, or Hybrid RAG fusion.
Deciding between private cloud, on-prem, or hybrid LLM infrastructure.
Mapping citation, explainability, and access control requirements.
What the
Assessment Answers
We determine the technical and operational levers that matter most for a reliable, production-ready RAG system.
Knowledge
Who This Offer Is For
Knowledge Owners
Teams managing fragmented documents across SharePoint, Confluence, or internal silos.
Regulated Buyers
Organizations in BFSI or Healthcare that require private or on-prem AI deployment.
Pilot Seekers
Teams ready to move from AI interest to a citation-backed production pilot.
Product Leaders
Groups building internal AI copilots or customer-facing knowledge assistants.
How the Assessment Works
Business Discovery
Understand what the organization wants RAG to do and identify the high-value use cases.
Source & Connector Review
Identify target repositories (SharePoint, Confluence) and connector feasibility.
Retrieval & Validation
Assess if you need Hybrid RAG, multi-layer verification, or standard retrieval.
Governance & Deployment
Review private infrastructure needs, multilingual support, and access controls.
Roadmap Delivery
Final recommendation on whether to proceed with a pilot, POC, or full build.
Common Starting Scenarios
Internal Knowledge Assistant
Evaluating source quality for a grounded, internal-facing AI copilot.
Support Knowledge Systems
Designing a RAG system for high-accuracy customer service resolution.
Enterprise Search
Modernizing search with citation-backed AI retrieval across siloed data.
Regulated BFSI/Healthcare
Assessing private or on-prem RAG needs for sensitive environments.
Connector-Heavy Rollouts
Planning integrations with SharePoint, Confluence, and ERPs.
Hallucination Control
Ensuring trust through source enforcement and verification logic.
Expected Outcomes
"Decision-ready output for citation-backed enterprise knowledge AI."
Retrieval Strategy
Clearly defined retrieval model (semantic vs hybrid) for your use case.
Source Audit
Detailed evaluation of knowledge source quality and repository readiness.
Deployment Map
Recommendation for SaaS, private cloud, or on-prem deployment model.
Control Framework
Mapping of citation, traceability, and governance requirements.
Execution Roadmap
Practical, phased implementation plan for pilot or full rollout.
Ready for
Enterprise RAG?
Book Assessment Why Choose
Mobiloitte?
We treat RAG as an enterprise search and knowledge architecture problem, not just a chatbot feature.
Hybrid Retrieval
Combining dense and sparse retrieval with multi-layer verification.
Private Deployment
Supporting on-prem and private cloud for BFSI, Healthcare, and Govt.
Citations-By-Design
Source enforcement and traceability built into the core architecture.
Enterprise Connectors
Direct integrations with SharePoint, Confluence, and internal repos.
Verification Layers
Multi-stage verification to ensure answers are grounded in your data.
Low-Cost Architecture
40-60% cheaper than LLM-only systems through smart orchestration.
RAG
Readiness
FAQ
"The success of RAG depends on source quality, not just LLM capability."
Find Out If You're
Ready for RAG
Discuss your repositories, deployment constraints, governance needs, and pilot goals with the Mobiloitte team before moving into implementation.