Expense Policy Decision Engine (Policy API Integration)

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This Expense Policy Decision Engine (Policy API Integration) template is a workshop that builds on the Threshold Memory version of the Expense Policy Decision Engine series of templates and introduces a simulated API integration. Instead of using a real external API, this class uses GLIK Knowledge to simulate an API response containing policy rules (such as spending thresholds and vendor blacklists).

Participants will:

• Learn how to use the Knowledge Retrieval Block to simulate calling an external policy API.

• Dynamically assign and evaluate retrieved rules in an expense approval workflow.

• Understand how internal knowledge objects can act as structured data endpoints.

This simulation sets the stage for connecting to real enterprise APIs in later stages.

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🛠️ What You’ll Build

A workflow that:

• Accepts an uploaded invoice file

• Extracts invoice metadata

• Retrieves policy rules (thresholds, blacklists) from GLIK Knowledge

• Applies conditional logic to approve, reject, or escalate

• Falls back to LLM reasoning if no rule applies

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🧩 Workflow Structure

Simulates an API integration using GLIK Knowledge. The uploaded invoice is extracted and evaluated against policy rules retrieved via a tag-based knowledge query. If the logic is ambiguous or unmatched, an LLM block provides fallback reasoning before issuing a final approval, rejection, or escalation decision.

📂 Step-by-Step Instructions

1. Create or Upload a Sample Policy in GLIK Knowledge

Create a new memory object with the following JSON content:

{
  "policy_id": "demo_policy_001",
  "threshold": 3000,
  "blacklist": ["ACME Consulting", "Shady Corp"],
  "categories": {
    "travel": 1000,
    "equipment": 5000
  }
}

Apply these tags:

• type:policy

• demo:true

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2. Build the Workflow in GLIK Studio

Required Blocks:

• 📥 Start

• 📄 Doc Extractor

• 🧠 Knowledge Retrieval Block (query: type:policy AND demo:true)

• 🧮 Conditional Block (compare values from invoice_data to policy_memory)

• 🤖 LLM Block (fallback)

• ✅ Answer or End Block

Variables Used:

• invoice_data

• policy_memory

• approval_result

• conversation_notes

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🧪 Practice Exercises

• Modify the policy memory with a tighter threshold

• Add a new blacklisted vendor

• Re-upload the workflow and re-run with different invoice PDFs to test the logic path

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🧠 Key Concepts

• Structured data in memory vs. static config

• Simulated API integration

• Conditional logic based on dynamic variables

• Querying GLIK Knowledge by tag

• Using fallback reasoning for exception cases

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📌 Next Steps

After this class, learners are ready to:

• Integrate real external APIs (e.g., using API Call blocks)

• Use branching logic to support multi-policy contexts

• Expand the workflow into a full Expense Audit Engine