> ## Documentation Index
> Fetch the complete documentation index at: https://docs.flowx.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent Builder use cases

> Real-world examples of what you can build with FlowX.AI Agent Builder.

Agent Builder supports a wide range of AI-powered automation scenarios. Below are the primary categories with examples drawn from production implementations.

## Document processing and extraction

Extract structured data from unstructured documents — invoices, contracts, shipping documents, financial statements — using Document Extraction nodes with tailored instructions per document type.

> [accordion] Logistics document processing
>
> An email-triggered pipeline processes carrier emails and their attachments:
>
> * **Classify** documents by type (BOL, invoice, rate confirmation, lumper receipt, fuel receipt, and more)
> * **Extract** structured fields from each document type using specialized TEXT\_EXTRACTION nodes
> * **Reconcile** extracted data against a Transportation Management System (TMS)
> * **Surface exceptions** for human review via task management
>
> **AI nodes used:** Document Extraction (12 document types), Custom Agent (12 comparison workflows, email summary)
>
> **Patterns involved:** [Fan-out extraction](https://docs.flowx.ai/6.x/ai-platform/patterns/fan-out-extraction.md), [AI comparison](https://docs.flowx.ai/6.x/ai-platform/patterns/ai-comparison-reconciliation.md)
>
> **Build it:** the [Reconcile supplier invoices against purchase orders](https://docs.flowx.ai/6.x/cookbooks/invoice-reconciliation.md) cookbook walks through a single-document version of this pipeline, step by step.

> [accordion] Mortgage document validation
>
> Process mortgage application packages by extracting product data from bank documentation:
>
> * **Extract** structured product details (interest rates, fees, insurance requirements) from bank product sheets
> * **Weight** income and debt values per bank-specific rules using AI extraction
> * **Validate** legal/regulatory eligibility using AI understanding
>
> **AI nodes used:** Document Extraction (income/debt/product extraction), Custom Agent (eligibility checks)
>
> **Patterns involved:** [Hybrid AI + business rules](https://docs.flowx.ai/6.x/ai-platform/patterns/hybrid-ai-rules.md), [Fan-out extraction](https://docs.flowx.ai/6.x/ai-platform/patterns/fan-out-extraction.md)

***

## Conversational AI

Build chat-based assistants that understand user intent, maintain conversation context, and provide personalized responses grounded in your data.

> [accordion] Mortgage advisor chatbot
>
> A conversational assistant that guides users through mortgage product selection:
>
> * **Detect intent** — classify user messages as greetings, product inquiries, data input, or other
> * **Route** to specialized handlers (small talk, personalized offers, knowledge base Q\&A)
> * **Generate** personalized mortgage consultant reports with comparative cost tables
> * **Maintain** conversation history across sessions
>
> **AI nodes used:** Intent Classification Agent (intent detection and routing), Custom Agent (responses, reports, knowledge base RAG)
>
> **Patterns involved:** [Intent classification](https://docs.flowx.ai/6.x/ai-platform/patterns/intent-classification-routing.md), [Knowledge base RAG](https://docs.flowx.ai/6.x/ai-platform/patterns/knowledge-base-rag.md), [Session state](https://docs.flowx.ai/6.x/ai-platform/patterns/session-state-management.md)

***

## AI-augmented decision making

Combine AI capabilities with deterministic business logic for auditable, explainable decision-making.

> [accordion] Product eligibility and scoring
>
> Evaluate financial product eligibility using a pipeline that mixes AI and business rules:
>
> * **AI extracts** income weights and debt factors from bank-specific rule documents
> * **Business rules** compute PMT, DTI ratios, maximum loan amounts, and currency conversions
> * **AI filters** products by qualitative criteria (loan type, sustainability features) with fuzzy matching
> * **Business rules** normalize scores and rank the top products
> * **AI generates** a professional consultant report with the final recommendations
>
> **AI nodes used:** Document Extraction (income weights, debt factors), Custom Agent (product filtering, report generation)
>
> **Patterns involved:** [Hybrid AI + business rules](https://docs.flowx.ai/6.x/ai-platform/patterns/hybrid-ai-rules.md)

> [accordion] Document reconciliation
>
> Compare AI-extracted document data against system-of-record values:
>
> * **Compare** field-by-field with structured exception reporting
> * **Generate** match rates and confidence scores per document
> * **Flag** mismatches, missing fields, and derived value discrepancies
> * **Route** exceptions to human reviewers based on severity
>
> **AI nodes used:** Custom Agent (comparison agents per document type)
>
> **Patterns involved:** [AI comparison and reconciliation](https://docs.flowx.ai/6.x/ai-platform/patterns/ai-comparison-reconciliation.md)

***

## Email automation

Process incoming emails and their attachments automatically using email triggers and AI workflows.

> [accordion] Carrier email processing
>
> Monitor an email inbox for incoming carrier communications:
>
> * **Trigger** workflows automatically when emails arrive (IMAP integration)
> * **Summarize** email content and classify intent (invoice submission, payment inquiry, dispute)
> * **Extract** and process all attachments through the document pipeline
> * **Look up** related orders in external systems (TMS) by BOL number
> * **Notify** relevant staff of exceptions via email templates
>
> **AI nodes used:** Custom Agent (email summary, comparison), Document Extraction (attachments)
>
> **Data sources:** Email Trigger, REST API (TMS), FlowX Database

***

## Building your own use case

**1. Identify the AI tasks**

Map which steps in your process need AI (extraction, classification, generation, comparison) versus deterministic logic (calculations, routing, validation).

**2. Choose your patterns**

Select from the [AI patterns](https://docs.flowx.ai/6.x/ai-platform/patterns/overview.md) that match your needs. Most apps combine 2-4 patterns.

**3. Design the data flow**

Define your data sources, data model, and how data moves between processes, workflows, and AI nodes.

**4. Build incrementally**

Start with a single AI node (e.g., one document type extraction), validate it works, then expand to the full pipeline.

**5. Add human review**

Use task management views for exception handling and quality assurance, especially for high-stakes decisions.

## Related resources

> [card] [Tutorials](https://docs.flowx.ai/6.x/ai-platform/tutorials/overview.md)
>
> End-to-end build guides based on production apps

> [card] [AI patterns](https://docs.flowx.ai/6.x/ai-platform/patterns/overview.md)
>
> Reusable architectural patterns

> [card] [Node types](https://docs.flowx.ai/6.x/ai-platform/agent-builder/node-types.md)
>
> Detailed node reference

> [card] [Using agents](https://docs.flowx.ai/6.x/ai-platform/using-agents/overview.md)
>
> Deploy agents in your apps


## Related topics

- [AI node types](https://docs.flowx.ai/6.x/ai-platform/agent-builder/node-types.md)
- [Agent Builder](https://docs.flowx.ai/6.x/ai-platform/agent-builder/overview.md)
- [Extract Data from File](https://docs.flowx.ai/6.x/ai-platform/agent-builder/extract-data-from-file.md)
- [Intent Classification Agent](https://docs.flowx.ai/6.x/ai-platform/agent-builder/intent-classification.md)
- [Agent typologies](https://docs.flowx.ai/6.x/ai-platform/patterns/agent-typologies.md)


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