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Enterprise AI Case Study

Enterprise AI Operations Hub

Client: Logix Global Logistics · Segment: Neural Query Pipelines · Published 2026-06-01

Enterprise AI Operations Hub
Inference Delay
42ms
Time Saved / Week
20+ Hrs
Dispatch Error Rate
0.0%

The Challenge

Logix Global operated multiple disconnected data sheets, transport manifests, and SQL servers containing dispatch logs. Fleet dispatchers spent hours cross-referencing warehouses manually, leading to shipment delays and routing conflicts.

The Solution

We built a unified AI Operations Hub combining manifests, vector embeddings, and RAG execution paths into a natural language search system. The platform runs a lightweight React frontend communicating with containerized FastAPI microservices; natural language queries are validated by parameterized checking loops before SQL execution to prevent command-injection.

The Outcomes

  • Instant Dispatch: Routing calculations dropped from hours to sub-minute loops
  • Natural Queries: Dispatchers fetch inventory status with plain-language phrases
  • Zero Injection: Secure routing loops isolate SQL queries from direct user input

Used Technologies

Next.jsFastAPILangChainOpenAI APIPinecone DBPostgreSQLDockerAWS