SLAtech Legal
89/100UPL-aware, conflict-check native, confidentiality-tier configurable
Reproducible 200-question Legal-specific eval harness. +21-point lift vs generic SLAtech-Business (68/100). Driven by UPL guardrails, conflict-of-interest checks, и confidentiality posture. Пара с umbrella eval scoreboard, Legal glossary и Legal FAQ.
| Category | Legal-tuned | Generic | Lift |
|---|---|---|---|
| UPL guardrails Hard-coded refusal к dispense jurisdiction-specific legal advice — вместо этого routed к lawyer-confirmation step. Generic chatbots happily improvise legal advice, exposing firm к malpractice. |
94 | 56 | +38 |
| Conflict-of-interest checks Pre-intake party-name search против firm's existing-client database. Generic chatbots collect intake без any conflict check (firm liability). |
91 | 52 | +39 |
| Confidentiality posture PII redaction at ingest, single-tenant option, attorney-client privilege metadata tag. Generic chatbots ship ноль redaction. |
90 | 62 | +28 |
| Matter-intake quality Structured intake captures jurisdiction, opposing party, statute-of-limitations clock, retainer-fee disclosure. Generic chatbots collect free-text only. |
88 | 71 | +17 |
| Citation discipline Refuses к cite case-law или statute numbers без source-anchor verification. Generic chatbots hallucinate citations (2023 ChatGPT-Mata sanctions story). |
84 | 78 | +6 |
UPL-aware, conflict-check native, confidentiality-tier configurable
Нет UPL guardrails, нет conflict-check, generic confidentiality posture
Strong UPL guardrails но нет FHIR-equivalent matter-intake schema, English-first
Will improvise legal advice (malpractice exposure), нет conflict-check, conversation cap
Per-vertical eval score — один input. Три других инструмента самообслуживания закрывают картину без звонка с продавцами:
Eval methodology — open-source. 200 sealed Legal-specific questions с LLM-as-Judge scoring на factuality, hallucination и confidence axes.