Document Processing in Chemicals
Chemical companies process millions of documents every day—Safety Data Sheets, Technical Data Sheets, batch manufacturing records, Certificates of Analysis, REACH registration dossiers, dangerous goods shipping declarations, quality control test reports, and TSCA compliance filings, the list goes on.
Documentation failures in quality and compliance records are among the most common regulatory inspection findings, and each one delays product release.
LandingAI transforms documents into highly accurate, verifiable, structured data so teams can reliably automate document-intensive workflows.
Why Agentic Document Extraction for
Chemicals
Traceable Outputs for Regulatory Audits
Every extracted value from batch records, safety data sheets, and compliance filings is grounded to a precise location in the source document, giving quality and regulatory affairs teams the data integrity trail that FDA inspections, REACH enforcement, and EPA audits demand.
Accurate across Chemical Document Complexity
Chemical documents span 16-section standardized safety data sheets, dense analytical test reports, multi-page regulatory registration dossiers, and handwritten batch records from manufacturing operations; agentic extraction handles all of them without document-specific configuration.
Speed That Protects Product Commercialization
Compressing document processing cycle times across regulatory registration, batch record review, and SDS maintenance reduces the administrative delays that hold up product launches, lot releases, and shipment clearances.
Built for Complex Chemical Documents
Intelligent document processing across specialty chemicals, agrochemicals, industrial gases, and chemical distribution is extremely difficult due to the sheer diversity of document types, the inconsistent layouts and the domain expertise required. Then add multiple languages, handwriting, photographs, scans and faxes to the complexity.
Accurate parsing of dense tables that span multiple pages and contain merged cells.
Single pipeline for image, slide, document, and spreadsheet file types with 1000+ pages.
Strong recognition of character-based languages, handwriting, checkboxes, stamps and signatures.
Schema-driven field extraction with visual grounding traceable to the original document.
Use cases
SDS & Product Safety Documentation
Extract hazard classifications, exposure limits, regulatory substance identifiers, and handling requirements from Safety Data Sheets, extended safety data sheets, and Technical Data Sheets across inbound supplier portfolios and outbound product documentation to maintain accurate, compliant product stewardship records.
Reduce time-to-market for new products by accelerating SDS preparation and regulatory review cycles
Cut regulatory affairs staff hours spent manually extracting and reconciling hazard data across supplier SDS portfolios
Minimize liability exposure from SDS errors with traceable, auditable extraction of hazard classifications and exposure limits
Batch Record & Quality Compliance
Extract process parameters, in-process test results, deviation descriptions, and operator sign-off records from batch manufacturing records, Certificate of Analysis documents, quality control test reports, and deviation investigation reports to support GMP compliance reviews and lot release decisions.
Accelerate lot release decisions by compressing batch record review and reconciliation cycle times
Reduce quality staff hours spent on manual batch record review and data transcription across production runs
Maintain the complete, traceable batch history that FDA inspections, customer audits, and product liability investigations require
Hazardous Goods Transport & Customs Documentation
Extract UN numbers, hazard classes, packing group classifications, and shipper declarations from dangerous goods shipping declarations, hazmat bills of lading, IMDG compliance certificates, and chemical customs declarations to ensure compliant transport across modes and borders.
Accelerate shipment preparation to protect delivery timelines and customer order fulfillment commitments
Reduce logistics staff hours spent manually classifying and documenting hazardous material shipments
Minimize penalties and shipment rejections from incomplete or inaccurate dangerous goods documentation
Trusted for Document-Heavy Chemical Industry Workflows
Agentic Document Extraction enables chemical companies to automate document-intensive processes that traditionally require manual review.
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →
Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →
Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →
ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →
I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
Very often a loan officer who gets a borrower a solid preapproval fastest earns the deal and the real estate agent’s referrals. Reconstructing income is the hardest part, and Agentic Document Extraction is the cornerstone to getting it right and traceable. Accurate data upfront means we can get a cleaner loan file to the underwriter and get to CTC faster. Get it wrong and everything downstream gets affected.”
View case study →Agentic Document Extraction has proven to be both accurate and easy to use. We are building on that foundation to deliver reliable, transparent, and scalable automation that our customers can validate and trust.”
View case study →Trust is the product. Accuracy alone isn’t enough at enterprise scale—what matters is provenance, traceability, and control. LandingAI gives us confidence that every extracted value can be traced back to its source, audited, and defended. That’s what makes it deployable in regulated, real-world environments.”
View case study →Our Plan Review Agent has a lot of complicated components under the hood: traversing building code knowledge graphs, reasoning across disciplines and sheets, assessing issues informed by historical projects. None of it works if we can’t trust what came off the page. ADE gave us a reliable foundation, so our team could focus on incorporating our team’s expertise into our compliance reasoning system.”
View case study →ADE has significantly outperformed other document extractors we’ve used. It has helped us build an Agentic RAG answer engine, based on unique healthcare institutional content, to offer instant, validated support to medical professionals at the point of care.”
View case study →I appreciate its reliability and the fact that they're constantly innovating with new models, which helps us work smarter. The service is essential for handling heavy workloads in financial institutions as it provides the necessary infrastructure for high accuracy and fast throughput. I also find it adaptable to specific use cases because they're always working on new models.”
We use LandingAI's Agentic Document Extraction to build pipelines that turn unstructured text into structured data. First, the NER (Named Entity Recognition) detection has amazing accuracy. Second, the OCR capability is excellent — earlier I had to run a separate PDF extractor for text plus a separate LLM with OCR to summarize images, and now it's one step. Third, the image boundary detection is a standout.”
We ran a structured bake-off: the same five PDFs (ranging from a 12-page slide deck to a 400-page machinery manual) processed through other products and Landing AI's Agentic Document Extraction (ADE). We scored each tool on four criteria: Table fidelity, Figure extraction, Chunk typing, Scale. Landing AI ADE was the only tool that scored well on all four.”
