Typical pilots run 6–12 weeks and focus on immediate indicators like feedback latency and engagement; as of Sep 2025, regionally reported pilots show measurable classroom changes within that window. We set KPIs before launch so outcome measurement is operational from day one.

 National reports and AI coordination documents from 2023 emphasise student-data protection and explainability; we supply a compliance checklist and implementation steps to align with those 2023–2024 policy priorities and your local governance requirements. You’ll get documented data flows and retention policies as part of the pilot.

Yes — pilots and industry write-ups highlight that Thai-language models and bilingual content are essential for adoption, and our standard content localisation process adapts materials to Thai language and curricula. That localisation is a core part of the initial scope and PD.

No. Evidence and UNESCO guidance show that successful deployments augment teacher capacity when paired with professional development; we co-design workflows so AI reduces routine tasks (like marking) and frees teachers for higher‑value instruction and remediation.

Outcomes vary by use case, but vendor and pilot reports include faster feedback cycles, reduced marking time and improved personalised learning gains — for example, a BytePlus adaptive case reported about a 35% improvement in outcomes in one deployment cited in 2024–2025 write-ups. We translate those findings into realistic KPIs for each school.

UNESCO and national reports note the digital divide; our pilots begin with a connectivity audit and propose offline-capable workflows or device-light interventions where bandwidth is limited. The audit informs the scope and helps prioritise infrastructure investments before scale.

We design integrations for common LMS patterns (Canvas/Moodle-style systems) and include rubric-aware grading and xAPI/SCORM-compatible dashboards as required. Integration scope is defined during the discovery call and piloting phase.