Tensorlake Early October Updates: Schema-Enforced Pipelines + Document Structure Intelligence

Hi there! 👋

Welcome to this month's Tensorlake updates! We're excited to share four major improvements that make document pipelines more reliable in production: schema-enforced extraction, pattern-based partitioning, header hierarchy correction, and tracked changes parsing for Word documents.

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🎯 The Highlights

Schema-Enforced Extraction with Outlines: Stop dealing with malformed JSON and hallucinated fields. Tensorlake + Outlines uses constrained decoding to guarantee every extraction matches your Pydantic schema—no regex cleanup, no retries, no manual corrections. Perfect for invoice processing, contract parsing, and claims workflows where schema violations break downstream systems. Read the blog → | Try the notebook →

Pattern-Based Partitioning: Extract exactly what you need without hard-coded page ranges. Use regex patterns to target specific sections (like "ACCOUNT SUMMARY" in bank statements) regardless of where they appear in the document. Layout-agnostic extraction that works across document variations and saves tokens by skipping irrelevant pages. Read the blog → | Try the notebook →

Header Hierarchy Correction: Automatic detection and correction of header depths across documents. Enable cross_page_header_detection=True to fix OCR mistakes where subsections get marked as top-level headers—critical for accurate RAG chunking, document outlines, and knowledge graph construction. Try the notebook → | Read the changelog →

Tracked Changes Parsing for Word Documents: Parse .docx files with complete revision history—insertions, deletions, and reviewer comments preserved as structured HTML. Essential for contract redlining, compliance audit trails, and collaborative workflows. Try the notebook → | Read the changelog →

💡 Community Highlights

New from the community: Check out how teams are using Tensorlake for insurance claims automation, contract analysis workflows, and financial report parsing in our Slack community.

Calling all enterprises: Are you building production document pipelines with Tensorlake? We're making Tensorlake even more enterprise-ready and have early access to upcoming features for partners. Get in touch →

Thank you for being part of the Tensorlake community. We're here to help you build document pipelines that actually work in production.

Cheers,
The Tensorlake Team