Compare Trellis with top alternatives in the document processing category. Find detailed side-by-side comparisons to help you choose the best tool for your needs.
Other tools in the document processing category that you might want to compare with Trellis.
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Extract structured data from documents using AI models trained on your specific formats. Automates form processing, invoice extraction, and contract analysis with 95%+ accuracy through custom model training and 16+ prebuilt models.
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Microsoft's document processing service with prebuilt and custom extraction models for forms, invoices, receipts, IDs, and contracts. Pay-per-page from $0.001/page for read. Custom model training available.
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AWS document processing service that extracts text, tables, forms, and structured data from scanned documents and images using machine learning. Pay-per-page pricing starting at $0.0015/page for OCR.
💡 Pro tip: Most tools offer free trials or free tiers. Test 2-3 options side-by-side to see which fits your workflow best.
Trellis supports a wide range of unstructured document types including PDFs (both native and scanned), image files such as JPEGs and PNGs, Microsoft Word documents, and spreadsheets. The platform's LLM-driven approach means it can handle documents with varying layouts, multi-page structures, and mixed content types within a single pipeline. This makes it suitable for processing invoices, contracts, medical forms, insurance claims, and regulatory filings without needing a separate template for each format.
Traditional OCR tools convert images to text but lack contextual understanding — they recognize characters without grasping what the data means. Trellis uses large language models to not only extract text but also understand document structure, classify content, and map extracted fields to user-defined schemas. This means Trellis can handle layout variations, interpret ambiguous fields, and produce structured output without requiring rigid, per-template configurations that break when document formats change.
Yes. Trellis offers custom schema mapping, allowing you to define exactly which fields to extract for each document type and how the output should be structured. This means you can tailor extraction pipelines to your specific business needs — whether you need invoice line items, contract clause identification, patient demographic fields, or regulatory filing metadata. The structured output can then be directly ingested into your downstream databases, ERP systems, or analytics tools via the REST API.
Trellis is built for enterprise-scale workloads and includes batch processing capabilities designed for high-throughput document pipelines. Organizations processing thousands of documents per day — such as insurance carriers handling claims or financial institutions processing loan applications — can ingest documents programmatically via the API and receive structured data in return. The platform is architected to scale with volume, making it appropriate for production workloads rather than one-off extraction tasks.
Trellis offers a free trial for evaluation purposes, allowing prospective customers to test the platform on their own documents before committing. Beyond the trial, pricing is custom and based on document volume and enterprise needs, so interested teams should contact the Trellis sales team for a tailored quote. This approach ensures pricing aligns with actual usage patterns rather than a one-size-fits-all tier structure.
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