OUR METHODOLOGY
A considered working process
Healthcare AI work is most productive when it begins with honest questions — about what the data contains, what clinical problems are worth addressing analytically, and what the realistic constraints are. Our process is structured around these questions, in sequence.
STEP 01
Assess your data foundation
Understand what your health data actually contains before committing to any analytical programme. This is often the most clarifying step in the entire process.
STEP 02
Navigate implementation decisions
Evaluate AI tools and vendors with independent guidance, covering clinical workflow, governance, and Singapore's regulatory context — before any procurement commitment is made.
STEP 03
Apply machine learning methods
With a clear data foundation and a well-defined clinical question, apply structured analytical methods — with transparent outputs and explicit limitation statements.
Clinical Data Analysis & Modelling
A structured engagement to apply machine learning methods to de-identified clinical or operational health data. Suitable for tasks such as patient outcome analysis, length-of-stay modelling, readmission risk stratification, or resource utilisation patterns. All work is conducted within agreed data governance protocols and with close input from your clinical and informatics teams.
Outputs are presented in plain language with clear caveats on model limitations and appropriate use. We do not produce results that overstate what the data supports.
What this service includes
- Scoping session to define the clinical question and data requirements
- Data review and quality assessment prior to modelling
- Selection and application of appropriate ML methods (documented and justified)
- Written report with findings, caveats, and conditions for appropriate use
- Presentation of findings to clinical and administrative stakeholders
Process overview
AI Implementation Advisory for Health Systems
Guidance for healthcare organisations evaluating or in the process of implementing AI-assisted clinical tools. Covers vendor assessment, workflow integration considerations, staff engagement, and governance requirements under Singapore's regulatory context. Delivered as a series of structured advisory sessions with written outputs at each stage.
Suitable for hospital administrators, clinical informatics leads, and digital health teams preparing for or reviewing an AI procurement or deployment decision.
What this service covers
- Vendor shortlisting criteria and assessment framework
- Clinical workflow integration analysis and risk considerations
- Governance and regulatory alignment (MOH AI guidelines, PDPA, HSA SaMD)
- Staff engagement and change management considerations
- Written advisory summary after each session
Advisory session structure
Health Data Readiness Assessment
A careful review of your organisation's health data assets, collection practices, and infrastructure to identify what is realistically available for AI applications and what foundational work may be needed first. Produces a written assessment with observations across data quality, completeness, access controls, and compatibility with common modelling approaches.
A practical first step before engaging any AI vendor or internal development resource — so that decisions are made on the basis of what your data actually contains, not what you assume it contains.
Assessment dimensions
- Data quality: completeness, consistency, and coding accuracy across key variables
- Access control infrastructure and de-identification readiness
- System interoperability and compatibility with standard modelling environments
- Identification of data assets that are ready for use and those that require preparation
- Written assessment report with observations and prioritised recommendations
Typical timeline
CHOOSING A SERVICE
Which service is right for you?
The services are designed to be taken in sequence, but each can stand on its own. This matrix helps identify the best starting point.
| YOUR SITUATION | Data Readiness | AI Advisory | Data Modelling |
|---|---|---|---|
| Unsure what your data contains or supports | — | — | |
| Evaluating an AI vendor or product | — | — | |
| Navigating MOH / PDPA governance requirements | — | — | |
| Have a defined clinical question and structured data | — | — | |
| Starting from scratch — want a complete picture first | — |
ACROSS ALL SERVICES
Standards that apply to every engagement
Data security & PDPA
All engagements governed by data handling agreements aligned with Singapore's Personal Data Protection Act.
Written scope agreement
Engagement scope, deliverables, and timeframe agreed in writing before any work commences.
Plain-language outputs
All written materials reviewed to ensure readability for clinical and administrative decision-makers.
Explicit limitation statements
Every analytical output includes clear documentation of what the analysis cannot determine and when results should not be generalised.
Collaborative working
Your clinical and informatics team is involved throughout — not consulted at the start and handed results at the end.
Vendor independence
No referral fees accepted; no preferred vendor relationships. Recommendations reflect only your data and objectives.
PRICING
Transparent starting fees
All prices are starting points for a standard-scope engagement. Final fees are agreed in writing after an initial scoping conversation — no surprises.
Data Readiness Assessment
SGD 580
Starting from
Written assessment report; 2–3 week engagement; suitable as a standalone first step.
EnquireAI Implementation Advisory
SGD 1,480
Starting from
4–6 advisory sessions with written outputs; 6–8 week engagement; suitable for teams actively planning an AI project.
EnquireClinical Data Modelling
SGD 2,700
Starting from
End-to-end analytical engagement; written report with findings and caveats; 5–7 week timeline for standard scope.
EnquireGET STARTED
Not sure which service fits your situation?
A short initial conversation often clarifies more than reading a detailed description. Share a little about your organisation and what you're working toward — we'll suggest the most appropriate starting point.
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