Our autonomous AI agents extract supplier data from PDFs, classify mixtures with a deterministic rules engine that gives the same answer every time, and draft review-ready SDSs in 25 or more languages. Your formulations stay completely private and your data stays under your control.
AI handles the reading and drafting. Classification uses a deterministic rules engine, not a probabilistic model. Your formulations remain yours: customer data never trains our models.
Convert supplier PDFs into structured data you can trust, with clear accuracy and confidence scores for each field. You can easily check what the AI found and review it fast. Move your old libraries in just weeks and build a solid base for your compliance program.
You don't need to enter data by hand or worry about hidden processes. Each step is handled by a dedicated agent, with a full audit trail at every stage.
Our extraction models are built for this task. They turn any supplier's SDS PDF into organized substance data, with field accuracy of 98% or better.
A deterministic rules engine applies GHS additivity, concentration cut-offs, and bridging principles per jurisdiction, with allergen and restricted-substance screening built in.
The classified data populates every section, and global GHS phrases are added in over 25 languages from a curated library.
A review agent checks each section, highlights confidence for every field, and clearly marks what needs your approval before publishing.
The system monitors OSHA, EPA, REACH, CLP, and other regulatory lists in every region you ship to. If a substance is reclassified anywhere, all affected SDSs are flagged automatically.
Our AI agents extract supplier data, apply jurisdiction-specific GHS rules using a deterministic engine, and generate review-ready SDSs in over 25 languages. This process delivers speed while maintaining accuracy and auditability.
Supplier PDFs are converted into structured data with high field accuracy and per-field confidence scores. You have full visibility into AI-extracted data, currently in use worldwide.
When regulations change in any market, affected SDSs in your library are flagged automatically.
Your existing SDS library imports through the indexing engine. Most teams are live before a legacy vendor would finish scoping.
AI handles reading and drafting, but does not classify information or provide final approval. Your team retains all decision-making, while routine typing and waiting are eliminated.
Request a demoLegacy platforms added AI as a feature on top of a database designed twenty years ago. Valenc was built around it from the start, so the agents read supplier documents, draft every section, and review the result inside the workflow, not in a side panel.
A separate review agent audits each draft, surfaces per-field confidence, and flags exactly what needs a human decision. Nothing publishes until a person approves it. Your steward sees what was extracted, reviews what was flagged, and gives the final approval.
Hazard classification never runs through a language model. A deterministic rules engine applies the published GHS rules for each jurisdiction, so identical inputs always give the identical result, and the rule that decided it sits right next to the answer.
How classification worksMonitoring agents watch OSHA, EPA, REACH, CLP, and jurisdiction lists worldwide. When a rule changes, the affected SDSs in your library are flagged automatically, and the updated rule ships as fast as the regulator publishes it, not on a quarterly release cycle.
How monitoring worksCompositions, documents, and everything else you load into Valenc are never used to train AI models, ours or anyone else's. Your data stays isolated to your account and is used only to do the work you ask for.
Built by people who spent more than ten years inside the legacy tools. Read the story behind Valenc.
Legacy compliance platforms restrict data access, requiring months of consulting to onboard and charging fees to export data. Valenc ensures your data moves freely in both directions. Export or integrate at any time, with no additional costs or obligations.
The SDS Indexing extraction engine processes your existing safety data sheets from any legacy system or template, converting them into clean, structured data.
All product data managed by Valenc is accessible externally. Connect your ERP, PLM, or custom tools to retrieve information as needed.
Valenc is an AI-native chemical compliance and SDS authoring platform for chemical manufacturers. It extracts data from supplier safety data sheets, classifies mixtures under GHS rules, and drafts review-ready SDSs across jurisdictions.
Valenc 1.0 will support over 80 jurisdictions, including the US, EU, UK, Canada, and Mexico, applying GHS classification rules specific to each region. This ensures a single product remains compliant wherever you operate.
Classification uses a deterministic rules engine rather than a probabilistic model. It applies GHS additivity formulas, concentration cut-offs, and bridging principles to ensure identical inputs always yield the same auditable result.
Valenc is designed for product stewards, EHS professionals, and regulatory teams at chemical manufacturers who manage safety data sheets across multiple products and jurisdictions.
Minutes. AI agents draft all 16 sections in over 25 languages, while a review agent highlights items requiring human sign-off. That is down from the one to two hours typical of legacy tools.
No. Your formulations, compositions, and documents are never used to train any AI models. Customer data remains isolated within your account and is used solely to fulfill your requests.
Implementation takes only weeks. Your existing SDS library is imported using the same extraction engine that powers SDS Indexing, so your current documents become structured starting data. There is no re-keying phase or extended consulting engagement.
Yes. A monitoring agent continuously tracks OSHA, EPA, REACH, CLP, and other regulatory sources, and automatically flags any SDS affected by rule changes.
Submit several supplier SDSs and receive them back as structured, classified, and review-ready data.
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