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Vietnam’s first curriculum-aligned
math AI foundation.

VietAlpha is CS Inspiration’s research and AI arm. The dataset is built to Ministry of Education and Training standards and structured across pretrain, fine-tune, and evaluation splits, so models built on it reflect how mathematics is actually taught and examined in Vietnam.

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A dataset, an evaluation, a path to deployment.

VietAlpha is CS Inspiration's research and AI program. It is Vietnam's first mathematics dataset aligned to Ministry of Education and Training standards, with pretrain, fine-tune, and evaluation splits ready for model development. The goal is to give Vietnamese educators, researchers, and AI builders a base layer that reflects how mathematics is actually taught and examined in Vietnam, instead of adapting foreign models that were never designed for this context.

The program is funded by AWS and runs on AWS infrastructure: SageMaker for compute and training, DynamoDB for user data, S3 for the math library, WAF and KMS for security. VietAlpha took first place in the Edtech category of the National Youth Innovation Award at UEH ICIA. First integration is planned through Numbers to Networks teaching sessions and through student partners at HCMUT (Ho Chi Minh City University of Technology).

1stCurriculum-aligned mathematics dataset in Vietnam
1st placeNational Youth Innovation Award, Edtech (UEH ICIA)
0International institutional partners
$0+Raised in pre-seed funding
Roadmap · 2026
  1. Feb 2026Scale data collection and training
  2. Mar 2026VietAlpha V1.0 prototype for testing
  3. Jul 2026Student integration into partner schools begins
  4. Oct 2026Iteration based on student and educator feedback
  5. Dec 2026Continue iteration while scaling

Methodology, partners, and architecture are on vietalpha.org. Dates reflect the plan and may shift.

Learn more at
vietalpha.org

Methodology, evaluation splits, partner institutions, and progress updates are on the dedicated site.

Open vietalpha.org
VietAlphaResearch · AI · VietnamBack to all programs