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<title>Agentic AI in Data Catalog System</title>
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<!-- SLIDE 1: Title -->
<section class="slide active" data-slide="1">
<div class="slide-content">
<div class="badge"><i data-lucide="sparkles"></i> The Next Evolution</div>
<!-- <h1 class="gradient-text">DataNexus:<br>Agentic AI Assistant</h1> -->
<h1 class="gradient-text">Agentic AI <br> in Data Catalog System</h1>
<p class="subtitle">Revolutionizing Data Discovery, Lineage, and Governance through intelligent agent orchestration.</p>
</div>
</section>
<!-- SLIDE 2: Overview -->
<section class="slide" data-slide="2">
<div class="slide-content">
<h2 class="gradient-text">What is a Data Catalog?</h2>
<p class="subtitle" style="max-width: 1000px; margin-bottom: 2.5rem;">
A <strong>Data Catalog System</strong> is a modern platform that gives organizations complete visibility into their interconnected data ecosystem. It enables businesses to integrate data from multiple sources
<span style="color: var(--primary); font-weight: 600;">(MySQL, MSSQL, Snowflake, Redshift)</span>
and provides a visual interface to explore, track, and ensure data accuracy through lineage, alerts, and notifications.
</p>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="search"></i></div>
<h3>Discovery</h3>
<p>Global asset searching across multi-cloud environments.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="git-branch"></i></div>
<h3>Lineage</h3>
<p>Deep-hop dependency tracking and impact analysis.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="activity"></i></div>
<h3>Health</h3>
<p>Real-time data quality scores and freshness alerts.</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 3: System Structure -->
<section class="slide" data-slide="3">
<div class="slide-content">
<h2 class="gradient-text">The Building Blocks</h2>
<p class="subtitle">Understanding the core structure of our data ecosystem.</p>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="box"></i></div>
<h3>Data Assets</h3>
<p>The individual "objects" in your catalog. <br><br><strong>Examples:</strong> <br>β’ Tables & Columns <br>β’ Databases <br>β’ Pipelines & Jobs <br>β’ Dashboards & Reports</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="network"></i></div>
<h3>Lineage</h3>
<p>The "Family Tree" of your data. It maps the flow from the <strong>Source</strong> to the <strong>Destination</strong>, showing exactly how datasets are connected and transformed.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="database"></i></div>
<h3>Metadata</h3>
<p>The "Identity Card" for every asset. It stores who owns the data, its current quality score, business tags, and technical schema details.</p>
</div>
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</section>
<!-- SLIDE 4: AI Features -->
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<div class="slide-content">
<h2 class="gradient-text">Introducing AI Features</h2>
<p class="subtitle">A comprehensive toolkit for autonomous data intelligence.</p>
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<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="users"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Multi-Agent System</h3>
<p style="font-size: 0.8rem;">Coordinated specialist network.</p>
</div>
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<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="brain"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Smart Query Understanding</h3>
<p style="font-size: 0.8rem;">Deep intent & semantic parsing.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="help-circle"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Clarification Handling</h3>
<p style="font-size: 0.8rem;">Resolving ambiguity via dialogue.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="repeat"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Multi-Step Reasoning</h3>
<p style="font-size: 0.8rem;">Autonomous ReAct Loop.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="layers"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Parallel Agent Execution</h3>
<p style="font-size: 0.8rem;">Multithreaded task fulfillment.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="history"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Memory & Context</h3>
<p style="font-size: 0.8rem;">Long-term conversation history.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="briefcase"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Workspace Awareness</h3>
<p style="font-size: 0.8rem;">Deep metadata & schema insight.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="filter"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Hybrid Search</h3>
<p style="font-size: 0.8rem;">Vector + Semantic + Structured.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="target"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Decision Making</h3>
<p style="font-size: 0.8rem;">Autonomous path selection.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="gantt-chart"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Task Decomposition</h3>
<p style="font-size: 0.8rem;">Breaking down complex goals.</p>
</div>
<div class="feature-card" style="padding: 1rem;">
<div class="icon-box" style="width: 2.5rem; height: 2.5rem; margin-bottom: 0.5rem;"><i data-lucide="coins"></i></div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Token Tracking</h3>
<p style="font-size: 0.8rem;">Transparent usage monitoring.</p>
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<div class="feature-card" style="padding: 1rem; border-color: var(--secondary-glow);">
<div class="badge" style="margin-bottom: 0.5rem; font-size: 0.5rem;">Future Scope</div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Write / Action Capability</h3>
<p style="font-size: 0.8rem;">Direct metadata modifications.</p>
</div>
<div class="feature-card" style="padding: 1rem; border-color: var(--secondary-glow);">
<div class="badge" style="margin-bottom: 0.5rem; font-size: 0.5rem;">Future Scope</div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Permission Control</h3>
<p style="font-size: 0.8rem;">Role-based governance.</p>
</div>
<div class="feature-card" style="padding: 1rem; border-color: var(--secondary-glow);">
<div class="badge" style="margin-bottom: 0.5rem; font-size: 0.5rem;">Future Scope</div>
<h3 style="font-size: 1rem; margin-bottom: 0.25rem;">Confirmation Flow</h3>
<p style="font-size: 0.8rem;">Human-in-the-loop validation.</p>
</div>
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</section>
<!-- SLIDE 5: Current AI Approaches -->
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<div class="slide-content">
<h2 class="gradient-text">How AI is Built Today</h2>
<p class="subtitle">Why most companies get stuck with basic tools that don't work for real business.</p>
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<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="message-square"></i></div>
<h3>Basic Chatbots</h3>
<p>Easy to build, but they often "make up" wrong answers because they don't really know your company's data.</p>
</div>
<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="git-branch"></i></div>
<h3>Simple Search (RAG)</h3>
<p>Good for basic questions, but it fails when you ask something slightly complex or when your data changes.</p>
</div>
<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="alert-octagon"></i></div>
<h3>The Big Problem</h3>
<p><strong>Too Rigid:</strong> These tools break easily. <br><strong>No Thinking:</strong> They can't fix their own mistakes or ask you for help.</p>
</div>
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</section>
<!-- SLIDE 6: What is Agentic AI? -->
<section class="slide" data-slide="6">
<div class="slide-content">
<h2 class="gradient-text">What is Agentic AI?</h2>
<p class="subtitle">The shift from "Static Retrieval" to "Dynamic Reasoning".</p>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="brain-cog"></i></div>
<h3>Cognitive Agency</h3>
<p>An AI that can "think" through a problem, decide which tools to use, and verify results.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="git-merge"></i></div>
<h3>The Basic Flow</h3>
<p>1. <strong>Plan:</strong> Decompose Query<br>2. <strong>Act:</strong> Use Expert Tools<br>3. <strong>Refine:</strong> Self-Correct</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="workflow"></i></div>
<h3>Stateful Logic</h3>
<p>Maintains memory throughout the loop to ensure no detail is missed during discovery.</p>
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</section>
<!-- SLIDE 7: Why Agentic AI? -->
<section class="slide" data-slide="7">
<div class="slide-content">
<h2 class="gradient-text">Why Agentic AI?</h2>
<p class="subtitle">Moving beyond traditional RAG limitations.</p>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="brain-circuit"></i></div>
<h3>Multi-step Reasoning</h3>
<p>Decomposes "impossible" questions into logical steps.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="help-circle"></i></div>
<h3>Human Clarification</h3>
<p>Asks for missing details instead of hallucinating.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="shield-check"></i></div>
<h3>Verification</h3>
<p>Agents cross-check results before returning to user.</p>
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</section>
<!-- SLIDE 8: Old Approach Architecture -->
<section class="slide diagram-slide" data-slide="8">
<div class="slide-content">
<div class="badge">Architecture: Legacy</div>
<h2 class="gradient-text">The Old RAG Pipeline</h2>
<p class="subtitle">A linear, one-shot retrieval flow.</p>
<div class="flow-container stagger-in">
<div class="flow-node">
<i data-lucide="search"></i>
<h4>Retrieve</h4>
<p>Vector Search</p>
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<div class="flow-connector"></div>
<div class="flow-node">
<i data-lucide="filter"></i>
<h4>Rank</h4>
<p>Generic Filter</p>
</div>
<div class="flow-connector"></div>
<div class="flow-node">
<i data-lucide="help-circle"></i>
<h4>Guess</h4>
<p>Direct Prompt</p>
</div>
<div class="flow-connector"></div>
<div class="flow-node" style="border-color: var(--danger);">
<i data-lucide="x-circle" style="color: var(--danger);"></i>
<h4>Output</h4>
<p>Static Answer</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 9: Old Approach Flow -->
<section class="slide" data-slide="9">
<div class="slide-content">
<h2 class="gradient-text">The Linear Flow</h2>
<div class="grid-cards stagger-in">
<div class="feature-card">
<h3>1. Retrieve</h3>
<p>Vector search finds chunks in workspace JSON.</p>
</div>
<div class="feature-card">
<h3>2. Rerank</h3>
<p>Cross-encoder filters for high similarity.</p>
</div>
<div class="feature-card">
<h3>3. Classify</h3>
<p>Hardcoded routing to Mongo or Python paths.</p>
</div>
<div class="feature-card">
<h3>4. Synthesize</h3>
<p>LLM summarizes the final context once.</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 10: Limitations -->
<section class="slide" data-slide="10">
<div class="slide-content">
<h2 class="gradient-text">Legacy Bottlenecks</h2>
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<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="alert-triangle"></i></div>
<h3>Zero Recovery</h3>
<p>If retrieval fails at step 1, the whole answer fails.</p>
</div>
<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="eye-off"></i></div>
<h3>Context Blindness</h3>
<p>Cannot handle complex dependencies across sections.</p>
</div>
<div class="feature-card" style="border-top: 4px solid var(--secondary);">
<div class="icon-box" style="color: var(--secondary);"><i data-lucide="user-x"></i></div>
<h3>Passive</h3>
<p>Guesses intent rather than clarifying with the user.</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 11: Agentic AI Architecture -->
<section class="slide diagram-slide" data-slide="11">
<div class="slide-content">
<div class="badge">Architecture: Modern</div>
<h2 class="gradient-text">The Agentic Graph</h2>
<p class="subtitle">Dynamic, stateful, and autonomous execution.</p>
<div class="hub-spoke-container stagger-in">
<!-- Central Hub -->
<div class="center-hub">
<i data-lucide="cpu" style="font-size: 3rem; margin-bottom: 0.5rem;"></i>
<h3 style="color: #fff; font-size: 1.2rem;">Orchestrator</h3>
<p style="font-size: 0.7rem; color: var(--primary);">Brain of the System</p>
</div>
<!-- Spoke Nodes -->
<div class="spoke-node" style="top: 10%; left: 20%;">
<i data-lucide="message-circle"></i>
<p>Clarification</p>
</div>
<div class="spoke-node" style="top: 10%; right: 20%;">
<i data-lucide="search"></i>
<p>Query SME</p>
</div>
<div class="spoke-node" style="bottom: 10%; left: 20%;">
<i data-lucide="bar-chart"></i>
<p>Analytics SME</p>
</div>
<div class="spoke-node" style="bottom: 10%; right: 20%;">
<i data-lucide="share-2"></i>
<p>Lineage SME</p>
</div>
<div class="spoke-node" style="right: 5%; top: 50%; transform: translateY(-50%);">
<i data-lucide="heart-pulse"></i>
<p>Health SME</p>
</div>
<!-- Reasoning Loop Indicator -->
<div style="position: absolute; width: 350px; height: 350px; border: 2px dashed rgba(6, 182, 212, 0.2); border-radius: 50%; animation: spin 20s linear infinite;"></div>
</div>
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</section>
<!-- SLIDE 12: Agents in System -->
<section class="slide" data-slide="12">
<div class="slide-content">
<h2 class="gradient-text">Agent Ecosystem</h2>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="cpu"></i></div>
<h3>Orchestrator</h3>
<p>The routing brain.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="helping-hand"></i></div>
<h3>Clarification</h3>
<p>The gap-filler.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="shield"></i></div>
<h3>Specialists</h3>
<p>The domain experts.</p>
</div>
<div class="feature-card">
<div class="icon-box"><i data-lucide="zap"></i></div>
<h3>Action</h3>
<p>The active executor.</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 13: Orchestrator Agent -->
<section class="slide" data-slide="13">
<div class="slide-content">
<h2 class="gradient-text">The Orchestrator</h2>
<div class="grid-cards stagger-in">
<div class="feature-card">
<h3>Context Injection</h3>
<p>Enriches query with history and database metadata.</p>
</div>
<div class="feature-card">
<h3>Intent Routing</h3>
<p>Classifies if the task is Read, Write, or Ambiguous.</p>
</div>
<div class="feature-card">
<h3>Task Splitting</h3>
<p>Parallelizes work across multi-threading specialists.</p>
</div>
</div>
</div>
</section>
<!-- SLIDE 14: Clarification Agent -->
<section class="slide" data-slide="14">
<div class="slide-content">
<h2 class="gradient-text">The Clarification Agent</h2>
<p class="subtitle">Guaranteed 100% precision through dialogue.</p>
<div class="feature-card" style="border-left: 6px solid var(--accent); background: rgba(245, 158, 11, 0.05);">
<div class="grid-cards" style="margin-top:0;">
<div>
<h3>Ambiguity Scoring</h3>
<p>If confidence < 0.5, it halts execution.</p>
</div>
<div>
<h3>User Engagement</h3>
<p>Asks for specific time-ranges, asset names, or columns.</p>
</div>
</div>
<div class="query-example" style="border-left-color: var(--accent);">
<span class="query-label">Dialogue Preview</span>
<strong>User:</strong> "Find the Sales table."<br>
<strong>Agent:</strong> "I found 3 tables related to 'Sales' which are named as 'marketing', 'sales_category1', 'sales_category2'. Which one should I analyze?"
</div>
</div>
</div>
</section>
<!-- SLIDE 15: Specialists -->
<section class="slide" data-slide="15">
<div class="slide-content">
<h2 class="gradient-text">Specialist Agents</h2>
<div class="grid-cards stagger-in">
<div class="feature-card">
<div class="icon-box"><i data-lucide="database"></i></div>
<h3>Query SME</h3>
<p>Factual lookup & Mongo query generation.</p>
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<span class="query-label">Example Query</span>
"List all columns in 'Users' with PII tags."
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<h3>Analytics SME</h3>
<p>Complex aggregations & success rate math.</p>
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<span class="query-label">Example Query</span>
"How many jobs failed in 'ETL_Main' today?"
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<h3>Lineage SME</h3>
<p>Traverses upstream/downstream flows.</p>
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<span class="query-label">Example Query</span>
"Show downstream reports for 'Order_Header'."
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<h3>Health SME</h3>
<p>Calculates freshness & quality scores.</p>
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<span class="query-label">Example Query</span>
"Is the 'Inventory' AWS Bucket stale?"
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<!-- SLIDE 16: Action Agent -->
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<h2 class="gradient-text">The Action Agent</h2>
<div class="badge" style="color: var(--secondary); border-color: var(--secondary);">Dev-Stage: In Progress</div>
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<h3>Active Modification</h3>
<p>Updating descriptions and tags via AI.</p>
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<h3>Security First</h3>
<p>Permission checks and Human-in-the-Loop confirms.</p>
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<h3>Audit Log</h3>
<p>Who, What, When tracking for all write actions.</p>
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<span class="query-label">Action Request</span>
<strong>User:</strong> "Set the owner of 'Payment_Gateway' to 'DevOps-Team'."<br>
<strong>System:</strong> "Permission verified. Requesting human confirmation..."
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<!-- SLIDE 17: ReAct Loop -->
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<h2 class="gradient-text">The ReAct Tool Loop</h2>
<p class="subtitle">The agents' inner monologue.</p>
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<h3>Reason</h3>
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<h3>Act</h3>
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<h3>Observe</h3>
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<p style="margin-top: 2rem; text-align: center; color: var(--text-muted);">Iterates up to 5 times to refine and verify facts.</p>
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<h2 class="gradient-text">Comparison: Old vs New</h2>
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<th>Feature</th>
<th>Old RAG</th>
<th>Agentic Assistant</th>
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<td>Logic Pattern</td>
<td>Static / Linear</td>
<td>Dynamic / Graph-based</td>
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<td>Multiple Tasks</td>
<td>Fail / Sequential</td>
<td>Parallel Specialist Dispatch</td>
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<td>Gap Resolution</td>
<td>Hallucinates</td>
<td>Clarification Agent Enquiry</td>
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<td>Consistency</td>
<td>Hit-or-Miss</td>
<td>High (via ReAct verification)</td>
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<!-- SLIDE 19: Query Performance Comparison -->
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<h2 class="gradient-text">Performance: Query Benchmarks</h2>
<p class="subtitle">Direct comparison across different query complexities.</p>
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<th>Query Type</th>
<th>Old RAG Approach</th>
<th>Agentic AI Approach</th>
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<td><strong>Basic Discovery</strong><br><small>"Find sales table"</small></td>
<td><span style="color: var(--danger);">β</span> Often Guesses Wrong</td>
<td><span style="color: var(--success);">β</span> Precise (via Clarification)</td>
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<td><strong>Multi-step Logic</strong><br><small>"Find 'Users' in Prod vs Dev"</small></td>
<td><span style="color: var(--danger);">β</span> Context Overflow</td>
<td><span style="color: var(--success);">β</span> Parallel SME Dispatch</td>
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<td><strong>Data Analytics</strong><br><small>"Success rate of Job X?"</small></td>
<td><span style="color: var(--danger);">β</span> Information Unavailable</td>
<td><span style="color: var(--success);">β</span> Real-time Calculation</td>
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<td><strong>Impact Analysis</strong><br><small>"Downstream of Column Y"</small></td>
<td><span style="color: var(--danger);">β</span> 50% Failure Rate</td>
<td><span style="color: var(--success);">β</span> Deep-hop Lineage Trace</td>
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</section>
<!-- SLIDE 20: Why Agentic > Simple Chat -->
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<h2 class="gradient-text">Agentic Choice: Beyond the ChatBot</h2>
<p class="subtitle">Why industrial data catalogs need "Agency," not just conversation.</p>
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<h3>From Answering to Solving</h3>
<p>A standard chatbot only predicts text. Our Agentic AI **decomposes complex goals** into logical steps to solve multi-hop data problems autonomously.</p>
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<h3>Active Tool Integration</h3>
<p>Instead of hallucinating facts, agents actively **execute specialized tools** (SQL, Python, Mongo) to fetch real-time, verified metadata.</p>
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<h3>Specialized Expert Swarms</h3>
<p>A simple bot is a generalist. We use **SME Agents** (Lineage, Analytics, Health) that act as individual domain experts for 100% technical accuracy.</p>
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<h3>Autonomous Path Selection</h3>
<p>Chatbots hit a dead-end if a query is ambiguous. Our system **self-corrects and pivots** to find alternative discovery paths or asks the user for missing info.</p>
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<h3>Self-Verifying Logic</h3>
<p>The **ReAct Loop** forces the AI to check its own work. If the observation doesn't match the plan, the agent refuses to guess and restarts the logic trail.</p>
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<h3>Enterprise Context Awareness</h3>
<p>Seamlessly integrates with **Workspace Metadata** and RBAC, ensuring that AI responses are contextually grounded in your specific industrial environment.</p>
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</section>
<!-- SLIDE 21: Closing -->
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<h1 class="gradient-text">The Future is Agentic.</h1>
<!-- <p class="subtitle">Beyond Conversation. Toward Autonomous Data Intelligence.</p> -->
<!-- <div class="badge" style="margin-top: 3rem;"><i data-lucide="mail"></i> Contact: Team DataNexus AI</div> -->
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</section>
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<div class="keyboard-hints">
<span>β β to navigate | SPACE to jump</span>
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