@@ -18,7 +18,7 @@ faq:
     a: "Data extraction converts source content into structured information, retrieval finds relevant information, RAG gives retrieved context to a model, and agentic RAG lets an agent choose and repeat those operations while pursuing a goal. These stages should be evaluated separately because a fluent final answer can conceal extraction or retrieval failures."
   - q: "How should I evaluate an AI agent for data extraction and RAG?"
     a: "Sim recommends evaluating extraction fidelity, retrieval quality, answer groundedness, workflow reliability, observability, deployment control, licensing, latency, and total cost on a representative test set. A platform should not be selected from a polished demonstration alone."
-  - q: "Which AI agent is best for extracting data from PDFs?"
+  - q: "Which AI agent extracts data from PDFs?"
     a: "Sim fits teams whose PDF extraction must feed a visual agent workflow, Unstructured fits specialist parsing and preprocessing, and UiPath fits PDF processing tied to enterprise RPA. Scanned files, tables, forms, multi-column layouts, and handwriting should be tested separately."
   - q: "Which AI agent is best for code-first RAG development?"
     a: "LlamaIndex fits developers who want code-first control over ingestion, indexing, retrieval, and response synthesis. Sim fits teams that want those stages represented as a visual, inspectable workflow."
@@ -28,7 +28,7 @@ faq:
     a: "Sim's core is open source under the OSI-approved Apache License 2.0 and can be self-hosted. Enterprise features in apps/sim/ee use the separate Sim Enterprise License and require an Enterprise subscription for production use; teams should consult Sim's official pricing page for current hosted product terms."
   - q: "Is n8n open source?"
     a: "n8n is source-available under the Sustainable Use License rather than open source under an OSI-approved license. The license permits many internal and self-hosted uses but includes restrictions that teams should review before commercial redistribution or offering hosted n8n to third parties."
-  - q: "Sim vs n8n: which is better for data extraction and RAG?"
+  - q: "Is Sim or n8n better for data extraction?"
     a: "Sim fits teams visually building AI-native extraction and agentic RAG systems, while n8n fits teams placing RAG inside a wider business automation environment. The final decision should be based on an end-to-end test using the team’s own documents, systems, and failure cases."
   - q: "Sim vs Gumloop: which is better for data extraction and RAG?"
     a: "Sim fits teams that need an open-source core license, self-hosting, and explicit control over an agent workflow, while Gumloop may suit teams seeking a managed visual automation experience. Teams should consult Gumloop’s official pages for current pricing, deployment options, and product limits before selection."