What we offer

Three engagement types. Each scoped for a specific stage.

Whether you're exploring ML viability, reviewing something you've already built, or ready for a full custom model — there's a structured path for each situation.

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How we work

Our methodology across all engagements

Regardless of which service you engage, the underlying approach stays consistent: understand the data first, define success criteria before modelling, and deliver something that holds up when scrutinised.

Data review & problem definition

We begin with the data you have and the outcome you need — before any modelling decisions are made.

Agreed criteria before building

Success metrics and acceptance thresholds are documented and agreed prior to the modelling phase.

Iterative development with reporting

Progress is shared throughout, not just at the end. Interim findings shape the direction of work.

Documented handover

All deliverables come with documentation structured for your team to use and maintain independently.

Solution 01

Custom ML Model Development

End-to-end development of a machine learning model tailored to your specific dataset and problem type — whether classification, regression, clustering, or recommendation. The engagement begins with a data review and problem definition workshop, followed by iterative model development, evaluation against agreed metrics, and documentation of the final model with deployment guidance. You retain full ownership of all code and trained artefacts. Suitable for teams with a clear business problem but limited in-house ML capacity.

Data review and problem definition workshop included

Supports classification, regression, clustering, and recommendation problems

Evaluation against agreed criteria, not default benchmarks

Full code, model artefacts, and documentation handed over

Deployment guidance included with final deliverable

Price

SGD 2,600

Enquire

Process overview

Data review and scoping workshop

Criteria and metrics agreement

Iterative model development

Evaluation and results review

Documentation and handover

Delivered within

2–3 weeks

From data access to final report. Scope variations may extend this slightly for particularly complex pipelines.

Solution 02

Model Evaluation & Improvement

A focused engagement for teams who already have an ML model in production or development but want an independent perspective on its performance, fairness characteristics, or generalisability. We review your training pipeline, test on held-out data, identify weaknesses, and provide a structured set of recommendations — some of which we can implement directly if preferred. Delivered within two to three weeks.

Independent review of training pipeline and data handling

Held-out data testing to surface real-world performance

Fairness and subgroup performance analysis

Structured recommendations report with prioritised fixes

Optional direct implementation of recommended changes

Price

SGD 980

Enquire

Solution 03

ML Proof of Concept

A contained, time-boxed build to explore whether a specific ML approach is viable for your data and use case before committing to a larger project. Includes data exploration, a working prototype model, an honest interpretation of results, and a recommendation on whether and how to proceed. Designed to reduce uncertainty in early-stage decision making without requiring a significant upfront commitment.

Data exploration and assessment included

Working prototype model with performance summary

Honest results interpretation — including "don't proceed" if warranted

Clear recommendation on next steps with rationale

Low commitment — the right starting point for first-time ML projects

Price

SGD 650

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Why start here?

Many teams spend months and significant budget building a full ML pipeline before discovering the data doesn't support the approach. The PoC engagement is designed to answer the foundational question — is this viable? — at a fraction of the cost and time of a full build.

Comparison

Which engagement is right for your situation?

Use this to identify the most appropriate starting point based on where your team is in the ML process.

Feature	PoC SGD 650	Evaluation SGD 980	Custom Build SGD 2,600
Best for	First ML project; testing viability	Existing model needing review	Clear problem, ready to build
Working model	Prototype	Reviews existing	Production-ready
Data needed upfront	Minimal	Existing model + data	Full dataset
Fairness analysis
Full documentation	Summary only	Recommendations report	Full model card
Typical timeline	1–2 weeks	2–3 weeks	Scoped at workshop

Standards

Technical and professional standards across all solutions

Data security & NDA

All engagements include a mutual NDA. Data is handled under strict confidentiality protocols and deleted at project close.

Performance standards

We define performance criteria with you before modelling — and evaluate against them rigorously, not against default benchmarks.

Responsive communication

Regular progress updates throughout the engagement. Unexpected findings are surfaced immediately, not held until final delivery.

PDPA compliance

All data handling practices align with Singapore's Personal Data Protection Act. Documented data processing records available on request.

Clean, reviewed code

All delivered code is reviewed internally before handover. Follows standard Python conventions with documented dependencies.

Scalability considerations

Models are built and documented with production constraints in mind — inference time, memory footprint, and update frequency are considered throughout.

Know which engagement fits? Or still deciding?

Either way, the next step is the same — a brief conversation about your problem. We'll help you figure out the right starting point.

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