RAGFlow is an open-source retrieval-augmented generation engine combining document parsing, retrieval and agent workflows.
Best for: Document retrieval pipelines with source references
About this listing
Product and access model reviewed from current official sources; workflow and example are editorial suggestions, not a hands-on test.
Official sourceDocument-AI tools for parsing, structured extraction, indexing, and building source-based agent workflows.
Best suited to
LlamaIndex suits developers turning documents into usable context or structured records.
LlamaIndex suits developers turning documents into usable context or structured records. Its ecosystem includes a developer framework and the commercial LlamaParse platform for document processing. Keep those offerings distinct: an open-source framework does not make the managed parsing service open source or remove model and infrastructure costs from an application.
This example describes a task, not a tested output. Adjust the source material and settings to your own situation.
Extract invoice number, supplier, currency and total from a supplied invoice. Return a missing value when the source does not support a field.
Result check: Compare values with the original page and check table structure and decimal interpretation before downstream use.
LlamaParse has recurring free monthly credits and paid usage tiers. It is a commercial service, separate from the open-source framework. Parsing modes and extraction consume credits; applications may also incur model, database and hosting charges.
Choose another workflow when its emphasis fits better: RAGFlow for another document-grounded retrieval workflow; Langflow for visual composition of model and retrieval components.
Layout-aware document parsing
Schema-based extraction
Document indexing
Document agent workflows
Developer framework integrations
LlamaParse has recurring free monthly credits and paid usage tiers. It is a commercial service, separate from the open-source framework. Parsing modes and extraction consume credits; applications may also incur model, database and hosting charges.
Plan information can change. Prices and conditions are set by the provider. Information checked 2026-10-15.
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LlamaIndex suits developers turning documents into usable context or structured records. Its ecosystem includes a developer framework and the commercial LlamaParse platform for document processing. Keep those offerings distinct: an open-source framework does not make the managed parsing service open source or remove model and infrastructure costs from an application.
LlamaParse has recurring free monthly credits and paid usage tiers. It is a commercial service, separate from the open-source framework. Parsing modes and extraction consume credits; applications may also incur model, database and hosting charges.
Choose the managed document service or the appropriate framework setup. Submit a small permitted document and define the fields or retrieval task.
Compare values with the original page and check table structure and decimal interpretation before downstream use.
RAGFlow for another document-grounded retrieval workflow; Langflow for visual composition of model and retrieval components.
Tell us what needs improving. No account or private output required.
Report incorrect information or a broken linkDocumentation-based review ยท 2026-10-15
Reviewed from the linked official documentation. The workflow and example are editorial suggestions; no account-level product test or measured performance comparison was performed.
RAGFlow is an open-source retrieval-augmented generation engine combining document parsing, retrieval and agent workflows.
Best for: Document retrieval pipelines with source references
Visual Python framework for building, testing, and serving AI agents and retrieval workflows with reusable components.
Best for: Python developers building visual agent and retrieval workflows
Backend for coding agents: model access, user login, Postgres and file storage under one project key, with a $0 starter.
Best for: Vectoree is for developers and teams whose coding agents, such as Cursor, Claude Code or Codex, build apps that need a backend.