Building Multi‑Scenario AI Assistants with Large Models at Huolala
Huolala, a logistics technology company, shares how it leverages large language models to create personal and office AI assistants across dozens of real‑world scenarios, detailing the underlying platform, prompt engineering, multimodal capabilities, multi‑agent coordination, and the resulting business empowerment.
Huolala, a logistics‑focused technology firm, has been exploring and applying artificial intelligence techniques based on large models to develop multi‑scenario personal and office AI assistants that improve efficiency and user experience.
The AI assistants combine intelligent dialogue, question‑answering, information retrieval (RAG), and agent technologies, offering 24‑hour continuous service and handling voice, text, and multimodal inputs.
Fourteen business scenarios covering 48 distinct needs have been explored, emphasizing simple direct QA, real‑world pain points, and broad applicability.
To address deployment challenges, Huolala built the self‑developed Wukong platform, a flexible LLM application platform that supports direct model calls, chain or agent construction, strong data security, customization, and rapid business rollout.
The platform offers various integration methods, such as Feishu bots, browser plugins (lalabot), and API endpoints, enabling quick connection to different systems.
The talk outlines five stages of AI‑driven business empowerment: (1) Professional assistants for specialized tasks, (2) AI QA assistants with precision handling, (3) Weekly‑report generation assistants that gather data, create charts, and draw conclusions, (4) Multimodal assistants for tasks like insurance quoting and training, and (5) Multi‑agent assistants that coordinate specialized agents (e.g., VPN, email, network) via a routing agent to improve overall accuracy.
Finally, the presentation looks ahead to the future of AI in logistics, invites questions, and includes a brief recruitment notice.
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Dedicated to sharing and discussing big data and AI technology applications, aiming to empower a million data scientists. Regularly hosts live tech talks and curates articles on big data, recommendation/search algorithms, advertising algorithms, NLP, intelligent risk control, autonomous driving, and machine learning/deep learning.
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