About
A team that grew out of group-level AI delivery
Synovate AI Pte Ltd is registered in Singapore (UEN 202608702E) with an engineering and delivery team in Changsha, China. We take on the engineering that turns AI into a system an organisation runs on.
Formerly Group AI Expert and Director of AI Innovation at CNGR Advanced Material Co., Ltd., where she drove group-level AI strategy and organisational build-out, internalised key AI capability, and established the company's first data governance framework, compute cluster and model lifecycle management system, taking several projects into industrial production.
Our vision: a patient-centred, end-to-end intelligent care system — and the same AI-native engineering method carried into manufacturing, education and public services.
More than a decade in process industry, having led the build and commissioning of control systems and data acquisition across multiple production lines. He owns the field and basic control layers: control scheme design, instrument and actuator selection, system configuration and loop commissioning, and getting field data up reliably and completely — a good model at layer three is worthless if what feeds it is wrong.
This is not a new pairing. The two worked together for two years and jointly delivered an AI expert system for a large pyrometallurgical production line: he owned control and data acquisition, founder Xiwen Liu owned the expert system, agent orchestration and process modelling. The upper and lower layers each have an equal owner, and the interface sits between two people rather than between two companies.
Four projects delivered in that role
Electron microscopy recognition
Image models quantify grain size, density, porosity and fines from micrographs, generate particle-size distributions automatically and accept manual correction; >80% model accuracy across product lines and 91.27% mean accuracy on sphericity.
Virtual laboratory
Process-data modelling predicting precursor properties from raw-material inputs, with driving-factor analysis (BET/PSD/TD/particle size, correlation and process-parameter effects), reducing trial-batch cost.
Innoscope
An LLM + RAG + agent intelligence core — search, industry radar, voice of customer and internal intelligence — closing the loop from collection through analysis to decision support.
Pyrometallurgical AI expert system
An AI expert system for a large pyrometallurgical production line covering process modelling, agent orchestration and a closed loop on field data — the largest AI project of her tenure, delivered over two years.
How we organise delivery
Prime contractor: the client is not the integrator
Control, software and AI vendors speak different languages and argue at the interfaces. With one prime contractor those arguments happen inside our team, and the client has one party to call.
Assemble the capability for the project, not the payroll
This kind of role pays off during construction; once the plant or the system is stable, demand drops sharply and keeping the headcount isn't economic.
More engineering per unit of budget
The Singapore entity handles proposal, compliance and the client interface; the China team handles engineering and delivery — typically three to four times the engineering output for the same budget.
Evidence first, scope second
Phase one ships the smallest loop that produces evidence. Whether to widen is the client's call, made after seeing real data.
Contact
Start with one conversation about the case
If you have a specific case — one production line, one faculty, one department, one clinical pathway — we'll do a feasibility conversation at no charge and tell you whether it's worth building.