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Guides, tutorials, and real-world workflows for composable document and image processing.
Building AI Agents That Process Documents: MCP, Structured I/O, and Confidence Routing
Build an AI agent pipeline that extracts document data, evaluates confidence scores, and routes to report generation or human review — using MCP and composable APIs.
Composable APIs vs. Point Solutions: Total Cost of Ownership for Content Processing
Multi-vendor stacks vs unified platforms — integration time, credential sprawl, billing reconciliation, and concrete TCO calculations for a typical 5-project agency.
Document-to-Markdown for RAG: Preparing Documents for Your AI Knowledge Base
Why markdown is the ideal format for LLM ingestion, how to preserve tables and layouts from PDFs, and how to build a document ingestion pipeline for RAG.
GDPR-Compliant Document Processing: Architecture Patterns for EU Companies
US CLOUD Act risks, zero-retention architectures, DPA requirements, and a practical framework for choosing EU-hosted vs US-hosted document processing services.
One n8n Node for Your Entire Document and Image Pipeline
Most n8n document workflows chain 3-4 separate services. The Iteration Layer community node replaces them with a single node that handles extraction, transformation, and generation.
How We Built Our Pitch Deck with Our Own API
We generated a 10-slide marketing deck using the Iteration Layer Image Generation API. No Figma, no PowerPoint — just JSON layers, layout compositing, and a mix task.
API Composability Patterns: How to Chain Iteration Layer APIs
When to pipeline, when to parallelize, and how to handle errors across chained API calls.
How We Generate OG Images with Our Own API
We use the Iteration Layer Image Generation API to create unique Open Graph images for every page on our site. Here's the exact implementation.
Why We Built Iteration Layer
Content processing is a mess of duct-taped tools. We built composable APIs that cover the full lifecycle: parse documents, transform images, render visuals.