AI for Legal Tech: Self-Hosted

Legal tech AI deployments have specific characteristics: client-confidential data, strict residency requirements, output that affects legal risk. Self-hosted on UK / EU dedicated GPU is materially better fit than hosted-API alternatives for regulated legal practice.

Workloads

• Contract review: clause extraction, anomaly flagging, redline suggestions
• Case-law research: semantic search over case databases + summarisation
• Document drafting: template-driven first drafts (NDAs, employment contracts, etc.)
• Discovery / disclosure: relevance classification across large doc sets
• Compliance review: policy applicability checking

Models

• Mistral Small 3 24B: strong English + European language legal reasoning
• Qwen 2.5 32B AWQ: alternative, strong multilingual
• R1-Distill-Qwen-32B: better on multi-step contract analysis
• BGE-m3: multilingual embeddings for case-law search
• Claude 3.5 Sonnet fallback: hardest cases (novel legal questions)

Train custom fine-tunes on firm-specific documents for brand-voice consistency in drafting (~£20 of GPU time, meaningful quality lift).

Compliance

• SRA outsourcing rules: single-tenant infrastructure simplifies oversight
• UK / EU residency: client data never leaves the perimeter
• Audit logging: every AI-assisted document change logged with hash + user + timestamp
• Privilege protection: AI tier inside the firm's perimeter; no third-party AI vendor in data path
• GDPR right-to-erasure: per-tenant collections + structured logs make deletion straightforward

Verdict

For UK / EU legal tech, self-hosted on dedicated GPU is the right architecture. The compliance fit is decisive; the cost economics are competitive; the quality on routine legal workflows is sufficient with hosted-API fallback for hardest cases. £500-1,500/mo SMB infrastructure replaces ~£3-10K/mo of hosted-AI legal tools.