[ Invoice Processing ]
Build document agents for invoice processing
LlamaIndex helps finance and ops teams parse invoices, extract data, and automate workflows — reducing manual entry and accelerating payments.
Challenge
Your invoices are everywhere. And they’re underused.
- Paper and PDF invoices scattered across systems
- Manual data entry leads to errors and delays
- Approvals get stuck in slow, human-driven workflows
- Legacy systems struggle with complex and changing layouts
Data
Clarity
Solution
Automate invoice parsing, validation, and approval workflows.
- Extract line items, totals, and metadata from invoices
- Validate vendor info and payment terms against contracts
- Flag discrepancies before processing
- Generate audit-ready invoice data automatically
Data
Chaos
Clarity
01
Invoice Parser
Extracts line items, taxes, and totals
02
Validation Agent
Checks invoices against purchase orders
03
Approval Assistant
Routes invoices to the right approvers
04
Audit Tracker
Prepares structured records for compliance reviews
Why Llamaindex
Trusted automation that understands how invoice processing work
Unmatched accuracy
LlamaCloud is purpose-built for complex documents with charts and tables.
Explainability
Citations, traceability, and confidence scores on every field
Developer-ready
Python and Typescript SDKs, APIs, and fine-tuned control.
Enterprise-scale
Handle thousands of reports with parallel pipelines
Compliant & auditable
For use in high-governance environments
Complete solution
Bring together document intelligence and agent workflows for end-to-end automation
How it works
From document chaos to agent intelligence
01
Upload documents (invoices, forms, contracts)
02
Parse and extract key information
03
Agents take action — route, validate, log, notify
04
Review or monitor via dashboards, API, or integrations
Trusted by analyst and QA teams at scale
Testimonials
As an Applied AI Data Scientist at one of the world's largest Private Equity Funds, I can attest that LlamaIndex's LlamaParse stands out as the premier solution for parsing complex documents in Enterprise RAG pipelines. Its exceptional handling of nested tables, complex spatial layouts, and image extraction is crucial for maintaining data integrity in advanced RAG and agent-based model development.
LlamaIndex’s framework gave us the flexibility we needed to quickly prototype and deploy production-ready RAG applications. The state of the art document parsing capabilities of LlamaParse have been particularly valuable – it handles our complex documents, including tables and hierarchical structures, with remarkable accuracy. The active community support and responsiveness of the LlamaIndex team meant we could quickly troubleshoot and optimize our implementations. What really stands out is how seamlessly we could customize the retrieval pipeline for our specific use cases while maintaining enterprise-grade performance. Salesforce Agentforce team has been leveraging LlamaIndex heavily.
LlamaCloud’s ability to efficiently parse and index our complex enterprise data has significantly bolstered RAG performance. Prior to LlamaCloud, multiple engineers needed to work on maintenance of data pipelines, but now our engineers can focus on the development and adoption of LLM applications.