Blog
Engineering deep dives, parsing benchmarks, and developer tutorials.
PeterParser vs LlamaParse vs Unstructured: 2026 Document Parsing Comparison
An honest comparison of the three most popular document parsing APIs in 2026. Table accuracy benchmarks, pricing breakdowns, feature matrices, and when to use each.
How to Build a RAG Pipeline with PeterParser in 10 Minutes
A step-by-step tutorial: parse PDFs, chunk for embeddings, and query with an LLM. Includes Python code, vector store setup, and production tips.
The True Cost of Document Parsing APIs in 2026
Pricing pages lie. Hidden costs, surcharges, and gotchas across 8 document parsing APIs. What you actually pay when processing 10,000 invoices/month.
Custom Output Templates: Why One-Size-Fits-All Extraction Fails
Every document is different. Here's how PeterParser's template system lets you define exactly what you want extracted — and why presets alone aren't enough.
Webhooks vs Polling vs SSE: Choosing the Right Approach for Async Parsing Results
Three approaches for knowing when your document is done parsing. Comparison table, code examples, and architecture recommendations.
How PeterParser Handles 1000-Page PDFs
Large documents overwhelm LLM context windows. Our chunked extraction strategy splits, parallelizes, and merges — automatically.
How PeterParser Achieves 99.5% Table Accuracy
Our three-stage pipeline separates document conversion, structured extraction, and source grounding. Here's why that architecture produces better results than single-pass approaches.