Domain

Defense & Chemical Safety Compliance

Platform

Centralized SDS Processing System

Services

  • AI/ML-Based Document Data Extraction
  • Computer Vision & OCR Integration
  • Predictive Hazard & Risk Analytics
  • Centralized Compliance & Workflow Automation
  • Cloud Migration & DevOps Support

Empowering Defense Through Intelligent Hazard Management

A leading defense organization faced delays and risks due to manual processing of hazardous chemical data from SDS (Safety Data Sheets). DASH built an AI-powered, cloud-native platform that automates data extraction, improves compliance, and accelerates workflows.

The solution boosts processing speed by 65%, cuts manual work by 80%, and saves millions annually. With advanced AI models, it delivers predictive insights and centralized access, enhancing operational readiness and safety.

About the Client 

A leading US defense organization driving air dominance, operational readiness, and chemical safety in critical missions.

Our experts built intelligent AI-driven automation, saving $5M+ annually.

Business Challenges

The client faced slow manual SDS (Safety Data Sheets) processing, high costs, and safety risks without a central system for compliance and quick decisions.

  • Inefficient Manual SDS Processing

    Reliance on labor-intensive, error-prone manual extraction slowed critical chemical data retrieval, delaying decision-making in defense operations. 

  • High Operational Costs

    Extensive manual workloads and fragmented data management resulted in excessive spending and resource allocation inefficiencies.

  • Risk of Non-Compliance and Safety Hazards

    Inadequate tracking and analysis of hazardous chemical information increased risks to personnel safety and regulatory compliance. 

  • Lack of Centralized, Scalable Solution

    Absence of a unified platform hindered real-time access, analytics, and adaptability to evolving SDS formats and regulations.

Vision-language models PaLI-X and Kosmos-2 decode complex text and images, powering predictive hazard analytics for superior safety. 

Our Journey with SDS Intelligence

Setting the stage

When a defense organization approached Dash to modernize their Safety Data Sheets (SDS) process, the request wasn’t just about technology. It was about reducing risk, saving time, and giving teams confidence that every SDS was complete, accurate, and ready for compliance checks.

We knew this couldn’t happen in one leap. Accuracy and trust are earned step by step. So, we worked in deliberate stages—building stability first, then adding intelligence, and finally aiming for foresight.

Phase 1

Building the Bedrock 

We started by creating a reliable, no-guesswork foundation. Instead of chasing flashy automation, we focused on getting the essentials right: clean text extraction, precise field detection, and clear validation points for human reviewers.

How we built it

  • Robust ingestion for both native PDFs and scans using PyMuPDF, pdfplumber, and Tesseract OCR with OpenCV preprocessing.
  • Deterministic parsing through regex and heuristic rules for CAS numbers, UN numbers, pH, and section headers.
  • Vendor-specific profiles to handle format quirks.
  • Visual detection of GHS pictograms with YOLOv5.
  • On-prem MLOps with Git for version control and auditability.

Impact

  • Our UX consultants conduct a 2-3 week discovery workshop to gather knowledge from all stakeholders. This helps us craft a holistic approach which will cater to all requirements.
Phase 2

Scaling with Intelligence 

We started by creating a reliable, no-guesswork foundation. Instead of chasing flashy automation, we focused on getting the essentials right: clean text extraction, precise field detection, and clear validation points for human reviewers.

How we built it

  • LayoutLMv3 & LILT for layout-aware extraction.
  • YOLOv8 sharper pictogram detection; DETR + TabStructNet for complex tables.
  • Semantic validation via RAG with Weaviate/Pinecone, supported by GPT-4 Turbo for context checks.
  • LangChain orchestration to chain extraction and validation steps with full explainability.
  • Fine-tuned chemical NER with Hugging Face Transformers.
  • Human-in-the-loop retraining using Label Studio feedback
  • Cloud-native MLOps on Azure for scalable, secure deployments.

Impact

  • The system adapted to unseen SDS formats with minimal manual intervention, while each reviewer correction directly improved future performance.
Phase 3

Shaping the Future 

Looking ahead, the goal is not just reading SDSs—it’s understanding them, predicting risks, and staying ahead of compliance changes.

What’s next

  • Multilingual parsing with NLLB / M2M100 for global coverage.
  • Vision-language models (PaLI-X, Kosmos-2) for richer hazard interpretation.
  • Autonomous agents (AutoGen, LangGraph) for end-to-end SDS handling with controlled human checkpoints.
  • Graph Neural Networks to map chemical relationships and predict hazard impacts.
  • Automated compliance mapping to OSHA, REACH, and GHS updates.
  • Federated learning to improve models without sharing sensitive data.
  • Edge AI nodes for air-gapped, on-site processing.

Impact

  • A proactive safety intelligence layer—multilingual, compliance-aware, and always learning-while keeping human oversight where it matters most.

Leveraging RAG pipelines and vector databases, our AI engineers ensure high-fidelity semantic validation and data integrity.

The Dash difference 

Through each stage, we didn’t just “deploy tech.” We partnered with our client, blending domain needs with technical expertise, and making sure every advancement aligned with their vision for safety and compliance.

Our guiding principles: 
  • Start with clear goals, not algorithms.
  • Keep every decision explainable and auditable.
  • Build for people first, then scale with tech.

Client Testimonials

The Dash team did an exceptional job and kept me involved at every stage, which was so important to me. Everyone, from the developers behind the scenes to the project team, played a critical role in bringing my app to life. I couldn’t be happier with my decision to partner with Dash and will continue working with them as the app grows nationwide.

- Kevin Unger | Experienced Medtech Executive & Entrepreneur

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