Thousands of daily emails for inquiries, quotes, and tracking create slow, costly, and error-prone manual work.
Delays in answering customers reduce satisfaction and trust, while personalization is hard to scale manually.
Without real-time analytics, logistics leaders struggle to forecast demand, optimize routes, and prevent delays.
Shipment records, emails, PDFs, and sensor data remain scattered, making integration and analysis difficult.
Building a Custom LLM for Enterprise Logistics
Continuous Data Curation and AI Training
AI-Driven Decision Support for Logistics Optimization
Enterprise-Grade Data Security and Compliance
Full-stack multimodal graph, human-in-the-loop learning, scalable + auditable.
Strong zero-shot generalization, though domain adaptation is limited.
Effective at transcription but weaker in case-level context.
Good for image attachments, yet limited in document structure understanding.
Handles multi-turn QA, but slowed by inference and context gaps.
Robust orchestration with retrieval, though multimodal fusion is still emerging.