Effectivelab ELS - Zazmic

Effectivelab ELS

Effective Laboratory Supplies (ELS) is a major industrial and laboratory supplier serving the global mining industry

Client:

Effective Laboratory Supplies (ELS)

Industry:

Industrial Supply / Logistics / Manufacturing

Core Technologies:

Background

Effective Laboratory Supplies (ELS) is a major industrial and laboratory supplier serving the global mining industry. With a massive inventory of over 20,000 items, ELS is a critical link in the mining supply chain, handling a constant stream of complex product inquiries and quotation requests.

Challenges

Despite their market-leading position, ELS faced operational bottlenecks that hindered growth and responsiveness:

  • Manual Matching: Extracting data and matching customer inquiries to the 20,000+ SKU catalog was entirely manual, causing significant delays in quote turnaround.
  • Data Ambiguity: Customer descriptions were often vague or non-standardized, increasing the risk of human error and costly rework.
  • Scaling Limitations: A reliance on paper-based and manual workflows meant the company could not increase inquiry volume without a linear increase in headcount.

Solutions Delivered

ELS partnered with Zazmic to design and deploy a cloud-native, AI-driven automation layer on Google Cloud. We moved the quotation process from a manual task to an intelligent, automated workflow.

Key solution components included:

  • Vertex AI Matching Engine
    Zazmic implemented high-performance vector search using Vertex AI to generate embeddings for the entire catalog, enabling near-instant semantic matching of ambiguous text to specific SKUs.
  • Intelligent Ranking & Scoring
    We developed a custom scoring algorithm that ranks the most relevant matches, allowing the system to “understand” industrial terminology even when customer descriptions don’t match the catalog exactly.
  • Salesforce Workflow Automation
    To ensure a seamless end-to-end user experience, we architected a data pipeline that integrates the AI engine directly with Salesforce, automating the flow from inquiry to quote.
  • Historical Validation Layer
    Our team built a validation engine that leverages historical match data to continuously refine model accuracy and ensure long-term reliability.

Outcomes

The collaboration resulted in a sophisticated, commercial-grade AI tool that has fundamentally changed ELS’s sales velocity. As a result of our collaboration, ELS:

  • Validated AI Matching at Scale: Successfully indexed and automated matching across 20,000+ SKUs with high accuracy.
  • Accelerated Quote Turnaround: Dramatically reduced the time required to move from customer inquiry to a finalized quotation.
  • Increased Capacity: Enabled the team to handle higher inquiry volumes and scale operations without increasing operational overhead.
  • Established a Foundation for GenAI: Set the stage for fully autonomous sales agents using fine-tuned Gemini models.

Conclusion

The partnership between ELS and Zazmic highlights the power of Generative AI to solve “unstructured” data problems in traditional industries. By bridging the gap between manual procurement and cloud-native automation, ELS has transformed its quotation process into a competitive advantage—moving from reactive manual work to a scalable, future-ready digital ecosystem.