AI that works
in production,
not just on paper.

We work with mid-to-large Malaysian enterprises and regional organisations that are investing in machine learning seriously — teams that have moved past initial experiments and need structured support to build reliable, maintainable AI systems. Our clients span financial services, logistics, manufacturing, and professional services sectors.

It depends on scope and your organisation's current state. A focused MLOps setup typically runs four to eight weeks. A data annotation strategy engagement might take two to four weeks. AI process mining projects often run six to ten weeks including data extraction, analysis, and reporting. We scope each project carefully before beginning.

Not necessarily. Some clients have established ML teams and engage us for specialist advisory on specific challenges. Others are earlier in their journey and value the structured methodology we bring. We tailor our involvement to what's actually useful in your context, rather than applying a fixed template.

Each service has defined deliverables. MLOps engagements conclude with a configured platform, operational runbooks, and team training sessions. Annotation strategy projects produce a labeling operations manual, tool configuration, and quality benchmarks. Process mining engagements deliver process maps, deviation reports, and prioritised optimisation recommendations.

Our listed prices reflect standard project scope. Engagements with significantly different scale or complexity may be priced differently after an initial scoping discussion. We prefer transparent, agreed pricing before any work begins, with no unexpected additions mid-project.

Yes. All client data and business information shared during an engagement is treated as confidential. We are happy to sign non-disclosure agreements before any substantive discussions begin, and we follow appropriate data handling standards throughout our work.