Knowledge
at work.

AwePlus deploys AKE, the Agentic Knowledge Engine, inside your enterprise: customised to your workflows, governed by your people, and run with our engineers in Taiwan, Malaysia, Australia and New Zealand.

The AI transformation delivery company of Magellan Global
Platform AKE, developed by Magellan Global with MTRI in Tokyo People Engineers and delivery managers in four countries Governance Human approval at every consequential decision

AI transformation is a change in how your people work. Not a demo.

Most enterprises already have models to choose from. What they lack is the engineering, the knowledge design and the operating discipline that make an AI workflow dependable inside their own systems and rules. That is the work AwePlus does.

The platform: AKE

The Agentic Knowledge Engine connects authorised knowledge sources, retrieval, agent-assisted tasks, human review and workflow integration. Magellan Global and MTRI develop it. AwePlus deploys it, customised to each enterprise.

The people: forward deployed engineers

Forward deployed engineers (FDEs) sit inside your team, in your systems and your meetings, and build the workflow with the people who will run it. Behind them stand solution engineers, integration developers and delivery managers in four offices, so the capability stays inside your enterprise rather than with a vendor.

The governance: responsibility at decision points

Permissions, approval steps and evaluation on your real cases. Suggestions are kept separate from approved actions, and every output can be traced to its sources.

Forward deployed engineering

Engineers inside your team, not advisers at a distance.

For AI DX in a B2B enterprise, the hard part is never the model. It is the hundred details inside your organisation: which document is current, who may approve what, how the ERP names a customer. A forward deployed engineer learns those details by working where they live.

Embedded

Works on site or in your daily stand-ups, with access agreed by your IT and compliance owners.

Hands-on

Configures AKE, writes the integrations and runs the evaluation set, then teaches your team to do the same.

Accountable

One named engineer per deployment, with a delivery manager and Taipei engineering behind them.

Illustration of the AwePlus team standing and sitting in front of a wall carrying the AwePlus logo
AwePlus team day in Taipei. Concept illustration.

AI DX services

From the first assessment to daily operation. Each service is scoped, priced and staffed as its own engagement, and all of them lead to the same place: AKE running inside your enterprise.

All services

Our core service

AKE customised enterprise deployment

A customised deployment of the AKE platform in your own environment: knowledge design, agent workflows, integration with your systems, evaluation on your cases, and a handover your team can run.

Your approval pointsGovernance
Your knowledge, your permissionsKnowledge
Your ERP, CRM, DMS and identitySystems

AI readiness and transformation planning

Choose the right first project before committing to an implementation.

Learn more

Agent workflows and process redesign

Connect knowledge, AI-assisted tasks and human decisions in a workflow your team will actually use.

Learn more

Knowledge and data foundation

Map sources, permissions and context so agents work from authorised, current information.

Learn more

Custom engineering and system integration

Make an AI application work with the ERP, CRM, document and identity systems around it.

Learn more

AI operations and continuous improvement

Keep a deployed workflow dependable as models, data and business needs change.

Learn more

AI DX capability building

Develop your internal AI transformation owner through supervised project work, in partnership with GSRP.

Learn more

How an AKE deployment runs

Four stages with a decision point between each. Durations are indicative; scope and fees are agreed before each stage starts.

1

Diagnose

2–4 weeks
  • Interview process owners and map the workflow.
  • Review data, systems, permissions and constraints.
  • Rank use cases and define a bounded pilot with acceptance criteria.
2

Design

3–6 weeks
  • Map knowledge sources and permissions.
  • Specify agent tasks, approval points and integration boundaries.
  • Build the evaluation set from your real cases.
3

Deploy

6–12 weeks
  • Configure AKE in your environment.
  • Build integrations and interfaces; test against the evaluation set.
  • Train users and go live on the agreed scope.
4

Operate

Ongoing
  • Named service owner, monitoring and support.
  • Change control when models, sources or rules change.
  • Improvement backlog reviewed with you.

Where AI DX starts, by industry

The first project is usually a repetitive, document-heavy workflow with a clear owner. These are the starting points we see most often.

Industry detail

Financial services and insurance

Claims handling, KYC and AML casework, policy servicing, regulatory reporting.

Legal and professional services

Matter intake, document review, research memos, client reporting, filing preparation.

Manufacturing and semiconductor

Engineering knowledge retrieval, quality and yield investigations, supplier documentation, maintenance records.

Healthcare and life sciences

Clinical documentation support, regulatory submissions, patient and provider services.

Retail, consumer and e-commerce

Customer operations, product content, returns and exceptions, merchandising decisions.

Logistics and mobility

Exception handling, customs and compliance documents, dispatch and scheduling support.

Public sector and education

Casework, citizen and student services, records management, policy research.

Technology and telecommunications

Support engineering, knowledge bases, internal developer and IT services.

Four countries. One delivery model.

Engineering in Taipei, with client services and delivery teams in Kuala Lumpur, Melbourne and Auckland. Every engagement follows the same Diagnose–Design–Deploy–Operate model, whichever office leads it.

Taiwan — Taipei

Engineering and delivery centre
10F, No. 50, Fushan Road
Beitou Shilin Science Park, Beitou District
Taipei City 112
Taiwan
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Malaysia — Kuala Lumpur

Client services and delivery, Southeast Asia
Level 22 (A-22-01 & A-22-12), The MET Corporate Towers
20, Jalan Dutamas 2, Kompleks Kerajaan
50480 Kuala Lumpur
Malaysia
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Australia — Melbourne

Client services and delivery, Australia
Level 2, T&G Building
161 Collins Street
Melbourne VIC 3000
Australia
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New Zealand — Auckland

Client services and delivery, New Zealand
50 Albert Street
Auckland CBD
Auckland 1010
New Zealand
Open in maps
Singapore — Magellan Global HQ Tokyo — MTRI research Taipei, Taiwan Kuala Lumpur, Malaysia Melbourne, Australia Auckland, New Zealand
AwePlus office Magellan Global group

Insights

Short, practical notes from deployment work.

All insights
18 September 2026 · 5 min read

The first AI project should be boring

The deployments that survive are the ones that start with a measurable, repetitive workflow and a named owner, not a showcase.

30 July 2026 · 5 min read

Knowledge before models

Most enterprise AI disappointment traces back to the information the system was given, not the model it ran on. What a usable knowledge foundation looks like.

Start with one workflow.

Tell us the process, the people who run it and what you would like to change. We will suggest the right first conversation, with no obligation.