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PandanCore
AI solutions overview
Our Solutions

Three Pathways to
AI Capability

Whether you need to understand where your organisation stands, build workforce skills, or put AI to work — Pandan Core has a structured path forward.

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How We Work

A Methodology Built Around Your Context

Every organisation that approaches AI adoption faces a different starting point. Some have pockets of early adoption but no coherent strategy. Others have leadership buy-in but workforce skills gaps. A few are ready to build but lack implementation guidance.

Pandan Core's approach begins with an honest assessment of where you are. From that baseline, we recommend the engagement path — or combination of paths — that will move you forward with the least friction and the highest chance of lasting change.

No pre-packaged engagements — scope is agreed jointly before work begins
Delivery teams include both AI practitioners and change management specialists
Progress is tracked against measurable outcomes agreed at project start
All engagements are grounded in Singapore regulatory and operational context
Pandan Core methodology
AI Readiness Diagnostic
Solution 01

AI Readiness Diagnostic

A structured assessment that maps your organisation's current AI posture across strategy, people, data, and technology. The Diagnostic surfaces gaps, opportunities, and readiness signals that often go unnoticed until an AI project is already underway — and struggling.

Outputs include a scored readiness profile, a prioritised action roadmap, and an executive briefing tailored for leadership decision-making. The process typically takes three to four weeks and engages stakeholders from IT, operations, HR, and senior leadership.

What the Diagnostic covers

Strategic alignment — does leadership understand AI's role in the business model?
Workforce capability — skills inventory by department and role cluster
Data foundations — quality, governance, and accessibility of key datasets
Technology landscape — existing tools, integration constraints, vendor relationships
Compliance and governance — alignment with PDPA, MAS guidelines, and sector requirements
Typical duration3–4 weeks
Engagement typeDiagnostic & Advisory
Key outputReadiness Roadmap
Best forPre-AI or early-stage orgs
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Solution 02

AI Workforce Training

Role-specific training programmes that build practical AI skills across your organisation — from executives who need to make informed decisions about AI investments, to front-line staff who will use AI tools daily, to technical teams building internal capabilities.

Programmes are designed around actual job functions, not generic AI overviews. Content uses your industry context, your tools, and realistic scenarios from your operational environment. Delivery can be in-person, hybrid, or self-paced depending on workforce distribution.

Programme tracks available

Executive Track — AI strategy, risk, governance, and investment decisions
Manager Track — leading AI-enabled teams, change management, performance frameworks
Practitioner Track — prompt engineering, AI tool use, output evaluation, workflow integration
Technical Track — model evaluation, API integration, fine-tuning, deployment pipelines
Typical duration4–12 weeks
FormatIn-person / Hybrid
Cohort size8–30 participants
Best forOrganisations scaling AI use
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AI Workforce Training
AI Solution Delivery
Solution 03

AI Solution Delivery

End-to-end design, build, and deployment of AI solutions scoped to specific business problems. Rather than selling a platform or tool, Pandan Core works on the challenge you need to solve — then selects and configures the appropriate approach, whether that means custom development, model integration, or configuring existing enterprise AI capabilities.

Every delivery project includes a documentation handover and a knowledge-transfer component, so your internal team understands what was built and how to maintain and extend it after the engagement closes.

Delivery process

1Problem framing and solution scoping workshop (1–2 days)
2Data audit and feasibility assessment (1–2 weeks)
3Prototype development and stakeholder review (2–6 weeks)
4Deployment, integration, and acceptance testing
5Knowledge transfer, documentation, and post-delivery support period
Typical duration6 weeks – 6 months
Pricing modelFixed-scope or T&M
OutputDeployed AI capability
Best forAI-ready organisations
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Find the Right Starting Point

Most clients begin with the Diagnostic, but some arrive having already completed internal assessments. Use this guide to decide where to start.

Feature / Consideration AI Diagnostic Workforce Training Solution Delivery
Uncovers hidden readiness gaps
Builds employee AI skills
Delivers a working AI product
Includes strategic roadmap
Suitable for first AI engagement
Requires data/tech readiness
Includes knowledge transfer
Engagement timeline 3–4 weeks 4–12 weeks 6 wk – 6 mo

Solutions can be combined or sequenced. Speak with our team to determine what makes sense for your timeline and budget.

Standards & Practices

How We Keep Quality Consistent

Data Privacy

All engagements are designed in compliance with Singapore's PDPA. Client data handled under signed NDA and data processing agreements.

Quality Assurance

Deliverables reviewed through an internal peer-review process before client submission. Findings independently validated on diagnostic engagements.

Client Alignment

Scope, success criteria, and expected outputs are agreed in writing before any engagement begins. No scope creep without mutual agreement.

Practitioner Standards

Team members hold relevant credentials across AI/ML, organisational development, and enterprise architecture. Continuous professional development is tracked.

Ready to Begin?

Not sure where to start?
That's what the Diagnostic is for.

Most clients find that an initial conversation — with no commitment required — is enough to identify the right engagement path. Reach out and we'll suggest a starting point based on where your organisation currently is.