SLAtech Edu
86/100FERPA-aware, prereq-reasoning native, multi-deadline modelling
Edu eval scoreboard
SLAtech Edu: 86/100
Reproducible 200-question Edu-specific eval harness. +16-point lift vs generic SLAtech-Business (70/100). Driven by enrollment-deadline awareness, FERPA-aware confidentiality, и course-prerequisite reasoning. Пара с umbrella eval scoreboard, Edu glossary и Edu FAQ.
Score breakdown по category
| Category | Edu-tuned | Generic | Lift |
|---|---|---|---|
| Enrollment-deadline awareness Bot quotes program-specific deadline + early-bird discount cutoff + late-fee schedule из authoritative source. Generic chatbots quote one generic deadline. |
90 | 67 | +23 |
| FERPA-aware confidentiality Identity-verification step перед disclosing GPA, financial-aid status или behavioural records. Generic chatbots over-disclose на impersonation attempts. |
92 | 58 | +34 |
| Course-prerequisite reasoning Multi-hop prereq chain (CS-201 requires CS-101 which requires Math-100). Generic chatbots dump full catalog. |
87 | 70 | +17 |
| Financial-aid intake quality Structured FAFSA / scholarship-eligibility checklist. Generic chatbots collect contact-info only. |
84 | 72 | +12 |
| Multilingual student support (HE / RU) Generic chatbots actually score higher здесь due к broader auto-translate coverage. Edu-specific terminology в HE/RU — continuing investment area. |
79 | 81 | -2 |
Competitor comparison
Intercom Fin (generic)
70/100Нет FERPA awareness, generic enrollment FAQ, English-first
AdmitHub / Mainstay (edu-native)
83/100Strong enrollment funnel но weaker FERPA-aware identity-verification, US-only deployments
Tidio Lyro (generic SMB)
62/100Нет FERPA, нет prereq reasoning, conversation cap на lower tiers
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Per-vertical eval score — один input. Три других инструмента самообслуживания закрывают картину без звонка с продавцами:
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Eval methodology — open-source. 200 sealed Edu-specific questions с LLM-as-Judge scoring на factuality, hallucination и confidence axes.