CxO Briefing: Data & Knowledge Management
75% Faster Knowledge Retrieval via RAG System
Data Analysis Knowledge Management Process
The Dragon1 AI BPMN Process Architect deployed a Retrieval-Augmented Generation (RAG) system, collapsing search time and delivering summarized, actionable insights to employees in natural language.
1. Current State (As-Is) - Manual Document Search
15 Minutes Per Search | Low Decision Speed
2. Future State (To-Be) - RAG Synthesis & Summary
3 Minutes Per Search | Contextualized Answers
Immediate Payback Justification
85% Modeling Efficiency: The Cost of Doing Nothing
75%
Reduction in time spent searching for internal information.
50%
Increase in employee satisfaction with internal knowledge bases.
Actionable
Insights synthesized from raw data, not just documents.
The Enterprise Result: Transformation Metrics
75%
Faster Knowledge Retrieval Time.
Directly improves employee productivity and reduces decision-making latency.
Summarization
AI Synthesizes Answers from Multiple Sources.
Employees receive a single, contextualized answer instead of a list of search results.
Security & Access
100% Role-Based Access Control (RBAC) Maintained.
The documented BPMN model ensured the RAG system strictly adhered to all necessary data security and access governance checks.
Detailed Process Comparison: Before and After AI
1. Current State (As-Is): The Information Silo
The initial process required employees to search manually across multiple, siloed databases, intranets, and file shares, resulting in an average search time of 15 minutes.
| Siloed Search Environment | Employees often had to repeat the same search query in three or more different locations to find an answer. | High search abandonment rate; inconsistent results and potential use of outdated data. |
| Manual Synthesis | After finding relevant documents, the employee had to read and synthesize the final answer manually. | Significant time lost in data interpretation rather than decision-making. |
2. Future State (To-Be): The 3-Minute AI Optimized Blueprint
The Dragon1 AI BPMN Process Architect generated the Future State model, implementing a centralized RAG system, achieving a 75% reduction in knowledge retrieval time.
| RAG-Powered Unified Search | A single query searches all necessary internal documents and uses Gen AI to synthesize a single, contextual answer. | 75% faster information access and higher answer consistency. |
| Automated Security Filter | The process includes an immediate, automated gate that filters results based on the querying user's access rights. | Guaranteed compliance with access policies and PII protection. |