SLAtech Edu
86/100FERPA-aware, prereq-reasoning native, multi-deadline modelling
Reproducible 200-question Edu-specific eval harness. +16-point lift vs generic SLAtech-Business (70/100). Driven by enrollment-deadline awareness, FERPA-aware confidentiality, and course-prerequisite reasoning. Pairs with umbrella eval scoreboard, Edu glossary and Edu FAQ.
| Category | Edu-tuned | Generic | Lift |
|---|---|---|---|
| Enrollment-deadline awareness Bot quotes program-specific deadline + early-bird discount cutoff + late-fee schedule from authoritative source. Generic chatbots quote one generic deadline. |
90 | 67 | +23 |
| FERPA-aware confidentiality Identity-verification step before disclosing GPA, financial-aid status, or behavioural records. Generic chatbots over-disclose on impersonation attempts. |
92 | 58 | +34 |
| Course-prerequisite reasoning Multi-hop prereq chain (CS-201 requires CS-101 which requires Math-100). Generic chatbots dump the 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 here due to broader auto-translate coverage. Edu-specific terminology in HE/RU is a continuing investment area. |
79 | 81 | -2 |
FERPA-aware, prereq-reasoning native, multi-deadline modelling
No FERPA awareness, generic enrollment FAQ, English-first
Strong enrollment funnel but weaker FERPA-aware identity-verification, US-only deployments
No FERPA, no prereq reasoning, conversation cap on lower tiers
The per-vertical eval score is one input. Three more self-serve tools complete the picture without a sales call:
Eval methodology is open-source. 200 sealed Edu-specific questions with LLM-as-Judge scoring on factuality, hallucination and confidence axes.