CHNAI LAB is a Cambodian student-run product studio. We turn focused product work into reviewable engineering experience: a person owns the decision, AI agents accelerate bounded work, and evidence determines what we can claim.
We are intentionally AI-native: agents help us research, build, test, document, and review, while humans stay accountable for product judgment, security, verification, and final decisions.
Most product source remains private. This profile exposes only approved direction, operating standards, and public proof—not customer data, private source, credentials, access state, or strategy.
These labels describe the evidence boundary as it exists now. They do not imply traction, legal ownership, production readiness, or a public release.
| Track | Direction | Evidence boundary |
|---|---|---|
| BayonHub | Opportunity coordination for Cambodian tech students. | Expanded MVP work exists on an unmerged review branch. End-to-end admin, employer, and student review, a merge decision, and deployment remain open. |
| Svaeng Yul | Mobile-first QCM practice for Cambodian medical and nursing students. | Restricted private medical QCM preview. Instructor review plus mobile and authentication validation remain open; it is not clinical guidance or a substitute for formal assessment. |
| Chomkar | B2B agriculture coordination where buyer requests can be documented and reviewed with farmers and cooperatives before harvest. | Live pre-pilot; no real order, validated demand, guaranteed price, sale, or impact claim. |
| Sat Digital | Defensive tooling concepts for Telegram communities, groups, and websites. | Working local prototype tested with synthetic fixtures only; no verified live integration, monitoring coverage, autonomous action, or protection guarantee. |
| Vantrex | Trading decision-support concepts for signals and indicator workflows. | Pre-launch. A public marketing surface does not establish a working application, validated model performance, or live-money capability. |
| PHSAROS | Point-of-sale, inventory, customer, and expense workflows for local SMEs. | A public product surface exists; fresh operator validation and written attribution remain open. No audited accounting, tax, payroll, or compliance claim. |
| Principle | Practice |
|---|---|
| Evidence before status | We separate deployed, local, simulated, degraded, and planned work. |
| Humans remain accountable | A person owns product judgment, verification, review, and the decision to ship. |
| AI stays bounded | Agents receive scoped context, never secrets, and their work remains reviewable. |
| Private by default | Source, credentials, user data, financial logic, and unreleased strategy stay out of public surfaces. |
| Credit is explicit | Contribution and product ownership are recorded decisions, not implications created by a profile or repository location. |
mainstays deployable.- Every meaningful change traces to an issue and pull request.
- Pull requests record human verification, AI involvement, risk, and rollback.
- Agents receive context, never secrets.
- Security-sensitive work stays private and follows the org security policy.
AGENTS.md— the vendor-neutral contract for AI agents in CHNAI LAB repositories.docs/AI_AGENT_WORKFLOW.md— the traceable issue-to-merge workflow for humans and agents.docs/REPOSITORY_STANDARD.md— adoption contract for every active product repository.docs/AI_CONCIERGE_STANDARD.md— public, product, and private agent boundaries.GOVERNANCE.md— roles, access, decision rights, and the current enforcement boundary.CONTRIBUTING.md— the path from a ready issue to a reviewed pull request.SECURITY.md— public/private reporting boundary.
ai-native-team-starter is a private product-neutral repository template
prepared for owner review and a separate publication decision.
It is not currently available for outside adoption. Any future public release
must first pass the repository's public-boundary and security review.
Live membership, invitations, security state, roles, and repository access are owner-managed on GitHub and verified privately. This public profile describes the operating model, not a current roster or access inventory.
If a repository is public, it should be safe for a recruiter, partner, student, or automated reviewer to inspect. Public content should show our standards, direction, and proof of work without overstating traction or leaking startup assets.
Browse the current public evidence and case studies at www.kavatana.me/projects.