Technology reshapes logistics
This article explains how AI technologies are applied to freight safety, detailing the challenges of traditional controls, the architecture of a real‑time AI safety system, data processing, risk detection, tiered interventions, and the resulting improvements in accuracy and operational efficiency.
LalaEval is a comprehensive human‑evaluation framework that tackles enterprise challenges in building domain‑specific large language models by automating QA set generation, reducing evaluator subjectivity through controversy and score‑fluctuation analysis, and providing extensible, data‑driven metrics for model construction and iterative improvement.
This article explores the practical application of Domain‑Driven Design and hexagonal architecture in a real‑world CRM system, detailing strategic and tactical design, module division, code examples, and a step‑by‑step migration from a traditional layered architecture to a more flexible, maintainable backend solution.
This article reviews the evolution of skeleton screens, explains their underlying principles, shares real-world case studies from Huolala, and provides practical guidelines for creating responsive, fine‑grained, and visually appealing skeleton screens that improve perceived performance without sacrificing actual load speed.
Huolala shares its LaLaEval framework, detailing how large‑model applications are evaluated through defined stages—background analysis, metric design, dataset generation, standards setting, and statistical analysis—while illustrating real‑world use cases in freight and driver invitation scenarios, and outlining future automation prospects.
This article details Huolala’s self‑developed Text‑to‑Speech system, outlining its architecture, the challenges of latency, naturalness, and language support, and the innovative solutions—including streaming synthesis, emotion modeling, and transfer‑learning‑based multilingual capabilities—that deliver more flexible and realistic voice interactions.
This article details Huolala's challenges in risk‑control testing amid rapid business growth, outlines the inefficiencies of manual configuration verification, and explains how a suite of automated tools and a full‑scope interception strategy dramatically improved testing efficiency, data quality assurance, and cross‑team collaboration.
Facing rapid growth, Huolala transformed its driver withdrawal flow from a manual, siloed PHP system to a Java‑based platform with automated risk controls, monitoring dashboards, and weekend payouts, achieving full‑order security, higher stability, improved driver satisfaction, and significant cost reductions.
This article examines the rapid growth of AI agents, outlines typical privacy and security challenges such as data leakage, model attacks, and prompt injection, and proposes comprehensive governance and technical measures to mitigate these risks in enterprise deployments.
This article details the design, architecture, and evolution of a self‑developed customer instant‑messaging system, covering its user‑centred philosophy, layered backend structure, technology choices such as WebSocket and Spring WebFlux, and how it solved challenges in gateway design, session storage, message ACK, and queue management to achieve high availability, security, and future‑ready scalability.
