Keep product meaning and authority explicit.
Product semantics, the Core–Shield boundary, evidence design and public claim discipline stay under a named architecture owner.
AEGI Labs
One team. Complementary technical depth.
Governance architecture, systems integration and interactive product engineering for controlled AI evaluation. Responsibilities are distinct; architecture, AI-assisted behaviour, evidence design and controlled-evaluation workflows are reviewed collaboratively.
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Three technical perspectives across one delivery model.
AEGI Labs combines product and governance architecture, systems integration, and human-centred product engineering so the same controlled-evaluation thesis can survive technical, operational and reviewer scrutiny.
Make the evaluation executable.
Model-output integration, API/data contracts, controlled replay, institution decision controls and technical evaluation stay connected to the same evaluation path.
Make evidence usable by reviewers.
Human–AI review experience, evidence visualisation and interactive prototyping translate system behaviour into a product surface people can inspect and challenge.
Team
Named accountability. Shared technical review.
The roles and experience below follow the final SFF/GFH 2026 pitch deck v0.5.2i. Primary accountability differs, while architecture, AI-assisted behaviour, evidence design and controlled-evaluation workflows are reviewed collaboratively.
01
AEGI LABS
Hoang Minh Truong
AI Product & Governance Architecture Lead
15 years across digital commerce, supply-chain systems and product development; formally trained in AI.
Leads AEGI product semantics, authority boundaries, Core–Shield architecture, evidence model, claim governance and roadmap.
02
AEGI LABS
Tri Minh Nguyen
AI Systems Architecture & Integration Lead
15+ years in scalable systems across healthcare and enterprise environments, including 5+ years in Singapore healthcare.
Leads model-output integration, API/data contracts, controlled replay, institution decision-control implementation and technical evaluation.
03
AEGI LABS
The Tinh Nguyen
AI Product Experience & Interactive Systems Lead
12 years in game and interactive-system engineering, including freelance work supporting Blizzard Entertainment and Grinding Gear Games.
Leads human–AI review experience, evidence visualisation and interactive prototyping.
Shared technical review
Different primary owners. One controlled-evaluation standard.
The team reviews architecture, AI-assisted behaviour, evidence design and controlled-evaluation workflows collaboratively, while each discipline retains a clear owner.
01
Product meaning. Shared Risk Context, authority boundaries and evidence claims remain coherent across product and public communication.
02
System behaviour. Integration, replay and decision-control behaviour are reviewed against the same institutional authority model.
03
Reviewer experience. Evidence is presented so risk, engineering and product stakeholders can inspect the same controlled story.
04
Next-stage discipline. The commercial ask remains one controlled evaluation before any production discussion.
BASEHo Chi Minh City, Vietnam
REGIONAL FOCUSSoutheast Asia
ENGAGEMENTControlled evaluations · Partnership and pilot discussionsDiscuss an engagement
AEGI LABS
Start with one defined workflow.
Bring the workflow, approved inputs and decision question. AEGI can then define the controlled evaluation before any production discussion.
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