Customersuccess stories
Better inventory positioning. Higher turnover velocity. More precise decision-making.
Procurement AgentCase Study
Client: FortuneTechgroup
Challenge
- No unified standard - risk assessment relies on individual experience. No structured, quantifiable rules.
- Siloed data, bogged down by manual data work- data is siloed across systems. Excessive time spent on manual gathering and calculation -instead of strategic sourcing.
- Procurement findings trapped- analysis and cross-functional discussions stay in chat logs and personal notes. No reuse.
Our Solutions: Intelligent Evolutionary Procurement Hub
- Automated Intelligence Preparation - automatically harmonizes inventory, demand forecasts, and purchase orders. Eliminates manual reconciliation and data cleansing.
- Expert-Level Decision Support - applies predictive models and business guardrails to identify sourcing risks. Delivers explainable, auditable approval decisions - not black-box answers.
- Continuous Learning Loop-every employee interaction refines the rule logic and retrains the model. The system gets smarter with each exception handled and every decision reviewed.
Value Delivery
- 30%-50% Sourcing Decision Precision
- Minimizes procurement mismatches (overbuying / underbuying)
- 20%-30% Capital Efficiency
- Accelerates inventory turnover velocity, lowers cash tied up in excess inventory
Beyond understanding: Enabling autonomous business through executable intelligence.
Maritime Agent HubCase Study
Client: SITC International Holdings
Challenge
- Data Silos & Semantic Fragmentation: Inconsistent data standards across multiple systems and a lack of a unified logic framework.
- Decision Latency: Heavy reliance on manual queries and expert analysis leads to delayed responses.
- Rigid Reporting: Static analysis tools lack the flexibility required for complex, real-time business scenarios.
- Hidden Losses: Inability to identify risks in a timely manner, resulting in lost opportunities and increased costs.
Our Solution: Maritime Agent Hub
A centralized intelligent decision-making hub built on a USL that bridges the gap from "Insight" to "Action":
- Core Engine: A USL Semantic Engine that serves as the "brain", unifying business logic mapping and modeling tools.
- Intelligent Interaction: Supports three proactive modes: Active Inquiry (Natural Language Processing), Real-time Insights (Agent-led monitoring), and Active Alerting (Smart push notifications).
- End-to-End Workflow: A complete pipeline including Multi-source Data Integration → Deep Insight Generation → AI-driven Recommendations → Actionable Tasks → Human-Machine Interaction.
Value Delivery
- Faster Decision-Making: Boosts decision speed by 70%+, capturing market opportunities faster.
- Revenue Growth: Enables precise performance improvements, uncovering 3%–8% in potential revenue.
- Risk Mitigation: Provides early warnings for 70%+ of abnormal events, significantly reducing losses.
- Customer Retention: Reduces lead attrition by 10%+, enhancing overall customer value.
- Operational Efficiency: Achieves cost reduction and efficiency gains, with a 50%+ increase in labor productivity.
Continuous production. Full-takt operation. Agentic MES delivers determinism.
Client: CATL (Battery manufacturing company)
Challenge
- Data & stability: 2B record limit causes crashes. Zero downtime tolerance in battery manufacturing.
- Global orchestration: Fragmented operations across regions, no unified control.
- Architecture rigidity: Monolithic systems cannot scale or evolve fast enough.
Our Solution: Agentic MES
- Rebuilt legacy MES into an Industrial Intelligent Management platform using composable architecture.
Value Delivery
- 99.999% system stability → Production continuity
- 9.6B+ data points → Performance at scale
- <0.4s Processing Time → High-takt line capable