Transforming Search Efficiency in the...

🚚 About the Customer

A leading logistics and supply chain management company that handles large-scale data communication between shippers, carriers, customs, and clients. Every day, their systems process millions of transactions—from Electronic Data Interchange (EDI) to request/response messages and structured XML files that power shipment updates, customs declarations, and supply chain milestones. Speed and visibility are crucial in logistics, where time lost in data retrieval can lead to shipment delays, compliance issues, and customer dissatisfaction.

❗The Challenge: Millions of Files, Zero Searchability

Imagine trying to find a single piece of paper in a room filled with millions of documents, every single day. That’s what this logistics company was facing with their digital file system.
Their back-end processes were generating millions of file transactions daily. These included:

• EDI documents for B2B communication
• XML files representing supply chain event messages
• Request and response logs tied to specific clients, orders, or shipment IDs

All of these were stored in Azure Blob Storage, a highly scalable cloud-based storage system. But with scale came chaos. Whenever clients or internal teams needed to retrieve a specific file, they had to:

• Manually browse folder structures
• Open files one by one
• Cross-reference metadata or filenames
• Raise IT support tickets for help

🔍 Key limitations:

• No content-based search: Couldn’t search inside files
• No metadata filters: Couldn’t find files by custom attributes like shipment ID, timestamps, or response code
• Slow retrieval: Searching often took hours, and sometimes days

This inefficiency was eating up valuable IT resources and slowing down operations in a high-speed industry.

💡 The Solution: Smart Search with Azure AI Search

To tackle this problem, Enkaytech implemented a scalable, intelligent search solution using Azure AI Search—a cloud-native search-as-a-service platform by Microsoft.

Here’s how we did it:

1️⃣ Connecting the Dots
We connected the company’s existing Azure Blob Storage and a supporting SQL metadata database to Azure AI Search.
This allowed Azure AI Search to:
• Crawl and index all stored files—EDI, XML, PDFs, etc.
• Read and analyze file content
• Extract and link metadata such as transaction type, client ID, timestamps, etc.

2️⃣ AI-Driven Indexing
Azure AI Search acted like a hyper-intelligent librarian. It scanned the content inside files—not just filenames—and built a searchable index that included:
• Keywords and text from documents
• Custom metadata tags
• Filenames and paths
Whether it was an EDI 214 shipment update or a customs clearance XML response, everything became instantly searchable.

3️⃣ User-Friendly UI
We built a sleek web interface that connects to Azure AI Search, allowing users to:
• 🔍 Search by keywords (e.g., PO number, client name)
• 📁 Filter by metadata (e.g., date range, file type, response status)
• 👀 Preview files inline
• ⬇️ Download results instantly

No more hunting for files or waiting for IT.

✅ Real-World Impact

The transformation was immediate and measurable:
⏱️ 95% faster search time
Users can now find any file in under 5 seconds—even from among millions.
📉 60% reduction in IT support tickets
Clients now self-serve using the portal. Fewer escalations to IT.
📈 100% search coverage
Every file and data point—old or new—is indexed and discoverable.
🚀 Scalable with growth

As the business scales, the AI-powered search scales automatically—no additional infrastructure needed.

One of the company’s client service leads shared:
“Previously, searching for one shipment response file could take us 3 hours. Now it takes less than a minute—and I can do it myself.”

📊 Why This Matters (Stats That Speak Volumes)

🧾 According to Gartner, poor data quality and searchability can cost organizations up to $12.9 million per year.
⚙️ The average employee spends 19% of their time searching for and gathering information (McKinsey).

🚚 In logistics, delays cost the global supply chain industry over $15 billion annually (Statista, 2023). Much of this is tied to poor visibility and slow response to disruptions.
By enabling fast access to file-level data, the company gained a competitive edge in transparency, speed, and service delivery.

🔄 The Bigger Picture

What started as a simple file search enhancement turned into a business accelerator. With better visibility and faster access to data:
• Internal teams responded to incidents faster.
• Clients were more empowered and satisfied.
• Data compliance and audit preparedness improved dramatically.
This is not just about search—it’s about giving people the right data at the right time, without the wait.

👨‍💻 Conclusion

Through our integration of Azure AI Search, this logistics leader turned a mountain of unsearchable data into an agile, AI-driven system that works like Google for their business files.