Our team recently visited a leading chemical enterprise for an AI technology exchange and hands-on workshop. Topics covered LLM applications, digital transformation, security governance and office productivity. We demonstrated our latest AI R&D results and discussed joint co-creation directions, helping a traditional chemical company cut costs, raise security and innovate with AI.
Part 1: Technical Sessions Building the AI Foundation
The exchange followed a three-level AI capability framework — from basic skills to advanced applications — covering the core knowledge points for enterprise AI adoption and building a complete theory-to-practice mental model.
Session 1: Prompt Engineering — Making AI Usable for Everyone
Starting from prompt engineering, we introduced the CREATE standardized framework covering context, role, expectations, action, tone and examples. Through graded exercises, participants quickly learned to write high-quality prompts, connecting daily document drafting, data analysis and information retrieval with AI tools.
Session 2: Skill Assetization — Turning Experience into Organizational Capability
Building on prompts, we introduced Skill assetization: packaging standard operating procedures, business experience and professional judgment into standardized, AI-executable skill modules.
We demonstrated the full Skill Hub workflow — from requirements and debugging to review, release and iteration — showing how scattered individual experience becomes reusable organizational AI assets. The core value: lower the barrier to AI usage and stop knowledge from walking out the door with staff turnover.
Session 3: Agents — Autonomous Execution, Extending AI Boundaries
The advanced session focused on agent technology. Unlike conversational interaction, agents combine four core capabilities — LLM, tool calling, memory and task orchestration — to autonomously complete complex operations.
Using real scenarios such as office automation, IT operations inspection and intelligent report generation, we demonstrated agents in action, while clarifying boundaries: standardized, repetitive work suits agents; core decisions and creative work remain human-led.
Part 2: Hands-On Demonstrations of AI in Production
After the theory, live demos: multiple AI applications already running in production, showing the customer team how AI moves from concept to real business value — higher efficiency, lower cost, less risk.
Demo 1: Intelligent Content Generation Assistant
A content automation tool for the security industry integrating multi-source collection, intelligent filtering, structured drafting and one-click publishing — dramatically shortening content production cycles.
Demo 2: AI Penetration Testing & Vulnerability Scanning
Chemicals demand the highest network and production security. We showed our AI security scanning tool: conversational automated penetration testing, port detection and vulnerability mining with live CVE feeds. Custom Skill modules constrain execution logic to avoid model hallucination; multiple rounds of target testing have proven its precision.
Demo 3: Automated IT Inspection
An AI-driven inspection tool that mimics operations-engineer workflows to automatically test web applications and services — scheduled runs, real-time alerting and automatic reports — upgrading reactive, manual checking into 7×24 proactive intelligent operations.
Demo 4: Internal Operations Management Platform
Addressing cumbersome legacy office systems, we demonstrated an operations platform built with Vibe Coding and AI agents — deeply integrating an AI assistant, operational analytics and advice, automatic work reports, AI-driven approval flows and email notifications, alongside hours management, ticketing and project tracking modules.
The platform is fully embedded in our daily workflow — proof of our "embrace AI, create value with AI" philosophy, and evidence that enterprises can build custom digital tooling with AI: self-controlled and iterated on demand.
Demo 5: Automated Vulnerability Management Platform
In security projects, vulnerability management involves massive data analysis, validation, grading and tracking. Our AI-built platform automates validation and classification, syncs results to a live dashboard, and generates AI analysis reports with remediation advice.
Since adoption, repetitive manual processing has dropped sharply while handling efficiency and data accuracy have risen — another example of our "AI-empowered security operations" strategy reaching real project pain points.
On-Site Interaction and Deep Exchange
In the discussion that followed, both sides explored practical AI adoption paths for traditional chemical enterprises. The customer raised real concerns — compliance governance, data security and employee usage policies — and our team answered each with delivery experience covering technology selection, platform build-out and supporting policies.
Part 3: Outcomes and a Long-Term Co-Creation Plan
Building on the exchange, core teams from both sides held a dedicated deep-dive on AI compliance, platform architecture, technical roadmap and implementation strategy, agreeing a long-term co-creation plan: jointly building a bespoke AI solution and intelligent architecture, an enterprise AI gateway and security operations platform — with data security and compliance as hard boundaries. AI will progressively land in contract review, supplier management, log analysis and office automation, through phased pilots, adaptation and all-staff training — creating a replicable digital solution for the chemical industry and steadily advancing intelligent transformation.