Three services, each
with a defined output
We build optimisation models, moderation systems, and ML infrastructure. Each service has a written scope, a clear timeline, and a production-ready deliverable.
Back to HomeHow every engagement is structured
Discovery
1–2 hour session to understand your data environment, systems, and the problem you need to address.
Scope document
Written scope defining deliverables, timeline, cost, and success criteria — agreed before work begins.
Build & review
Phased development with regular check-ins. You're informed at each milestone, not just at delivery.
Handover & support
Full documentation, handover session, and 30 days of post-delivery support included.
Supply Chain Optimisation Modelling
We build optimisation models that balance cost, speed, and reliability across your supply chain network. The service uses constraint-based and ML-driven approaches to evaluate routing, inventory placement, supplier selection, and demand allocation. Deliverables include a simulation environment and a set of recommended configurations.
Suitable for logistics companies, retail operators, and manufacturers dealing with multi-location inventory or supplier complexity. Engagements span 8–14 weeks.
What's included
- Network analysis and baseline model
- Constraint-based optimisation for routing and inventory placement
- ML-driven demand forecasting component
- Interactive simulation environment (transferred to client)
- Recommended configurations with trade-off analysis
- Documentation and handover session
Process steps
Data audit — review historical order, routing, and inventory records
Network mapping and constraint definition with your operations team
Baseline model build and initial optimisation runs
Simulation environment development and scenario testing
Configuration review with stakeholders
Handover session and documentation delivery
Automated Content Moderation
We develop custom moderation models for your platform — detecting policy violations, harmful content, spam, and misinformation across text, images, or video. We handle taxonomy definition, training data curation, model development, confidence-threshold tuning, and human-in-the-loop escalation workflows.
Suitable for social platforms, marketplaces, and community forums. Southeast Asian multilingual content — Bahasa Malaysia, English, Mandarin — is handled as a first-class concern. Engagements span 6–10 weeks.
What's included
- Taxonomy definition aligned with your platform's policies
- Training data curation and labelling
- Custom classifier model for your content types
- Confidence-threshold tuning to manage escalation volume
- Human-in-the-loop escalation workflow design and setup
- API endpoint or batch processing pipeline
Process steps
Policy and taxonomy workshop with your trust & safety team
Sample content review and labelling scheme development
Training data curation and quality checks
Model training, evaluation, and threshold calibration
Escalation workflow configuration and integration testing
Deployment, monitoring setup, and documentation handover
MLOps Pipeline Setup
We establish the operational infrastructure your team needs to develop, deploy, and maintain ML models systematically. The service covers experiment tracking, model versioning, CI/CD for model code, containerised serving, monitoring, and alerting. We integrate with your existing cloud provider and development tools.
Designed for engineering teams moving from notebook-based development to production workflows. Typical setup is 4–7 weeks.
What's included
- Experiment tracking setup (MLflow or equivalent)
- Model versioning and artefact registry
- CI/CD pipeline for model training and deployment code
- Containerised model serving infrastructure
- Monitoring dashboards and alerting configuration
- Integration with your existing cloud (AWS, GCP, or Azure)
Process steps
Audit of current development workflow and infrastructure
Tool selection and architecture design based on your stack
Experiment tracking and model versioning setup
CI/CD pipeline build and serving infrastructure deployment
Monitoring and alerting configuration
Team walkthrough, documentation, and handover
Which service fits your situation?
Use this to identify which engagement is most relevant to your current challenge.
| Supply Chain Modelling |
Content Moderation |
MLOps Setup |
|
|---|---|---|---|
| Best suited for | Logistics, retail, manufacturing | Platforms, marketplaces, forums | Engineering teams with ML models |
| Starting price | MYR 7,800 | MYR 5,400 | MYR 3,300 |
| Timeline | 8–14 weeks | 6–10 weeks | 4–7 weeks |
| Simulation environment | — | — | |
| Human-in-the-loop workflow | — | — | |
| CI/CD pipeline | — | — | |
| 30-day post-delivery support | |||
| Documentation & handover |
Technical and operational standards across all services
Version-controlled artefacts
All code and model artefacts are version-controlled and transferred to repositories you own.
Evaluation before delivery
Models are evaluated against agreed metrics. Results are documented and shared before delivery is confirmed.
NDA and PDPA compliance
Mutual NDA signed before data is shared. We operate under Malaysia's PDPA 2010. Data deleted after delivery.
Full documentation
Architecture, data schemas, model behaviour, and operational runbooks are delivered with every project.
Cloud-agnostic
We work across AWS, GCP, and Azure. We adapt to your environment — not the other way around.
30-day support window
Post-delivery support to address any issues arising from the work we've done. Included at no additional cost.
Not sure which service fits your situation?
Get in touch and describe your challenge. We'll identify whether one of our services is a good fit, or whether a scoping conversation would help clarify things.
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