Without changing a single line of existing code, our standardized AI enhancement middleware injects intelligent decision-making and automation capabilities into your after-sales platforms and supply chain management systems. From diagnosis to go-live in as fast as 2 weeks.
Your systems have served you for years, but data is dormant and staff are doing repetitive work. Rebuilding from scratch is too costly.
Existing systems carry years of workflows and data. Replacing them means million-level investment, half-year implementation cycles, and full staff retraining.
After-sales, supply chain, and warehousing systems operate in isolation. Data cannot flow, yet AI needs data scattered across multiple systems.
Customer service answers the same questions daily, engineers manually enter work orders, and management compiles reports by hand. Human effort is wasted on low-value tasks.
AI tools are purchased but cannot integrate with business systems. Staff must switch between multiple systems, and efficiency drops instead of rising.
Medical industry data is highly sensitive, requiring AI capabilities to support on-premise deployment. Generic SaaS cannot meet audit and privacy requirements.
AI projects often start at hundreds of thousands, but results are hard to quantify. Decision-makers worry about wasted investment.
Like adding an intelligent driving module to a car — we attach an AI brain to your existing business systems
Connect to existing business systems via API gateway or database views, without modifying any original system code. Your after-sales management and supply chain platforms continue running stably while AI runs as an independent enhancement layer.
Employees can access AI capabilities directly from their phones without downloading new apps. Deep integration with WeCom, DingTalk, and Lark puts the AI assistant right inside everyday communication tools, responding to business needs anytime, anywhere.
Smart Q&A, data extraction, auto decision-making, predictive analysis, report generation — five standard modules available on demand. Combine them like building blocks to get the AI functions you need.
Support on-premise deployment (data never leaves the factory), hybrid cloud (sensitive data local, compute in cloud), and pure SaaS — meeting security compliance requirements across industries.
Enterprise-grade audit logs record every data access, decision logic, and output by AI. Supports operation rollback, graded permissions, and compliance report export — meeting stringent medical industry regulatory audit requirements.
Data desensitization engine automatically identifies sensitive fields and processes them before transmission and storage. Tenant-level data isolation ensures physical separation. In on-premise mode, data never leaves the internal network.
From first contact to continuous operation, each phase has clear deliverables and acceptance criteria
A Real POC Schedule Reference (Intelligent Work Order Classification)
| Timeline | Activities | Deliverables |
|---|---|---|
| Day 1-2 | Requirements interview + data receipt | POC Scenario Confirmation |
| Day 3-4 | Data cleansing + knowledge base construction | Cleansed dataset |
| Day 5-7 | Middleware config + Prompt tuning | Runnable Demo |
| Day 8-10 | Blind test + accuracy optimization | Test Report V1 |
| Day 11-12 | User trial + feedback collection | User feedback record |
| Day 13-14 | Report preparation + demo presentation | POC Effectiveness Validation Report |
Flexibly combine AI modules according to your business needs, gradually expanding the scope of intelligence
For medical device after-sales scenarios, AI automatically completes work order classification, smart dispatch, fault prediction, and knowledge recommendations.
Voice/text describing the fault
Extract model, fault type, urgency
Match best engineer, auto assign
We understand the stringent data privacy and audit compliance requirements of the medical industry, offering a full spectrum from fully private to cloud-elastic deployment
Rapid activation, pay-as-you-go, zero maintenance. Ideal for businesses with lower data sensitivity who want to quickly validate AI value.
Sensitive business data stays local while AI computing and model inference run elastically in the cloud. Balances security and cost-effectiveness.
AI middleware and large models fully deployed on enterprise-owned servers or private cloud. Data never leaves the internal network, meeting the highest security compliance requirements.
Typical effects of the AI enhancement layer based on actual deployed project data
Tell us your business scenario. Our consultants will reach out within 24 hours
to craft a tailored intelligence solution for you.
Tel: +86 21 6841 3125
Email: customer@dataforhealth.cn
Address: Room 411, 515 Huanke Road, Pudong New Area, Shanghai
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