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From 10 minutes to 10 seconds
per Safety Data Sheet
StarTex Software's SDS library system required 10 minutes of manual extraction per Safety Data Sheet — reading 18 GHS sections, locating hazard codes, CAS numbers, and emergency procedures by hand. A Nanonets agentic pipeline now ingests, parses, and extracts all fields in 10 seconds with 96% confidence, auto-approving 90% of fields with no human touchpoint.
StarTex Software builds EHS software for companies managing chemical safety and compliance. Their SDS library module needed to ingest Safety Data Sheets from hundreds of manufacturers — each in a different layout — and extract structured hazard data for the compliance database. Manual processing created a bottleneck that limited the system's scalability.
The Problem
StarTex Software's SDS library module received Safety Data Sheets from hundreds of chemical manufacturers. Every SDS follows the 18-section GHS standard — but each manufacturer formats it differently. Extracting hazard statements, CAS numbers, and emergency procedures by hand took 10 minutes per document. With thousands of SDS documents to process, this created a compliance bottleneck.
- —10 minutes of manual extraction per SDS — reading 18 GHS sections to locate key fields.
- —Varied manufacturer formatting — different fonts, layouts, and languages for the same GHS structure.
- —No structured output— extracted data couldn't be reliably loaded into the compliance database.
What used to take our team 10 minutes per SDS now takes 10 seconds. Nanonets reads all 18 sections, extracts everything we need, and flags the few fields it's unsure about.
The solution
One SDS agent. 18 sections. 10 seconds.
Nanonets replaced the manual extraction loop with one agentic pipeline. Four agents each own one step: receiving SDS uploads from the StarTex EHS application, parsing all 18 GHS sections regardless of manufacturer format, extracting hazard statements, CAS numbers, and emergency procedures with confidence scoring, and writing approved records to the SDS library — with flagged fields routed to human review.
Pipeline overview
Impact
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