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Enterprise AI Services

Turning frontier AI potential into real-world ROI growth. Rejecting hollow "PPT concepts" and cheap wrappers — partnering with boards and leadership to map the path forward.

Service Type 01

AI Product Co-Creation

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Target Client

Medium-to-large enterprises with cutting-edge business ideas but lacking in-house algorithms and product teams

Problem Addressed

External outsourcing vendors do not understand the characteristics of LLMs, resulting in delivered products that are merely "wrapper websites" or riddled with LLM hallucinations, making them extremely difficult to deploy to a production environment.

Delivery Timeline2 - 3 months (depending on the complexity of the solution)
Cooperation ModelJoint Product Co-Creation / Phased Milestone Payments / Tech-for-Equity Joint Operation
Deliverables
High-Fidelity AI Product Prototype Design & Core PRD
Production-Grade MVP Platform Featuring a "Human-AI Collaborative Fallback Mechanism"
Complete Model Selection & System Distillation White Paper, plus Full-Stack Source Code
Implementation Steps

Clarify and pinpoint genuine pain points (rejecting thin wrappers to ensure AI is the optimal solution);

Agile Development: Deliver a v1.0 prototype in the initial phase, leveraging high-frequency data to validate the logic in an offline sandbox;

System Refinement: Establish exception fallback strategies and deliver a full suite of production-ready assets.

Enterprise FAQ

Common questions on agile LLM implementation, hallucination prevention and ROI measurement.

Who owns the intellectual property of a co-created project?

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Submit the intent form below — I will respond within 24 hours with an initial recommendation or a free 30-min video assessment.

School-Level Data-BI Cockpit Development for Jiao Tong University Affiliated Primary School
2026-07-20

School-Level Data-BI Cockpit Development for Jiao Tong University Affiliated Primary School

Achieving closed-loop data governance across multiple school systems through AI-powered smart import, data validation, and dynamic dashboards.

Education DigitalizationData Middle PlatformAI Smart ImportBI DashboardData GovernanceSmart Q&A

项目背景

交大附小 Data-BI 是面向学校管理场景建设的数据融合分析平台，目标是把分散在多个业务系统中的文件、表格、统计口径和管理数据统一接入，通过 AI 解析、人工复核、质量校验和可视化看板，形成可追溯、可分析、可运营的校级数据视图。

客户挑战

学校业务数据分散在多个系统和文件中，人工汇总成本高。
PDF、Excel、Word 等材料格式不统一，字段口径难以标准化。
数据导入后缺少统一校验机制，异常字段和低置信度数据不易发现。
管理层需要通过看板快速查看导入进度、数据质量和业务趋势。
一线人员希望能用自然语言询问数据，而不是手动查表和筛选。

解决方案

Data-BI 以“智能导入 + 数据校验 + 动态看板 + 智能问答”为主线，构建学校数据治理工作台。平台支持按用户权限动态加载可操作系统，上传业务文件后由 AI 进行字段识别和结构化抽取，再通过红绿灯置信度机制辅助人工核对，确认后的数据进入统一数据表，并同步支撑驾驶舱图表、统计卡片、质量报告和问答分析。
智能导入：支持业务系统选择、文件上传、格式预检和 AI 解析。
字段治理：通过库表维护配置字段、别名、校验规则和展示顺序。
质量校验：用高、中、低置信度标识提示人工重点复核。
动态看板：基于已入库字段生成统计卡片、表格和 ECharts 图表。
智能问答：支持围绕本地业务数据、当前看板、知识库和附件进行问答。
权限管理：按后台用户分配可导入和可操作的系统范围。
知识库能力：支持学校资料沉淀，为问答和解释提供上下文依据。