Legalica Model Amicus v.3.1
Meet our current legal AI model. Engineered to deliver precise, citation-backed legal answers and drafts across 324 jurisdictions and 187+ languages. Anchored by RAG and designed for strict enterprise data privacy.
A Safe, Grounded Approach to Legal Intelligence
Standard large language models often struggle in legal scenarios due to hallucinations, lack of localized statutory knowledge, and data privacy issues. Legalica model Amicus v.3.1 resolves these problems through a rigorous separation of generative capability and verified primary legal sources.
By combining a high-performance transformer architecture with our dynamic multi-jurisdictional RAG (Retrieval-Augmented Generation) pipeline, Amicus v.3.1 ensures that every generated statement is anchored in real, active legislation and case law precedents. The underlying weights are specifically fine-tuned for high precision in legal reasoning, regulatory classification, and contract drafting.
Engineered Capabilities
324 Jurisdictions Coverage
Trained on primary statutory data, administrative regulations, and case law precedents across continental civil law, common law, EU law, Sharia law, and East Asian frameworks.
187+ Languages & Dialects
Full cross-lingual semantic search capability. Query in one language (e.g. English) and search statutes written in another (e.g. Japanese or German) without losing legal meaning.
Anti-Hallucination Guardrails
The Retrieval-Augmented Generation (RAG) system anchors every output token to verified primary legal registers, systematically reducing the hallucination risk inherent in raw LLMs.
Zero-Data Retention
Client interactions, queries, and uploaded documents are processed in transient memory and never used to train AI models — under contractual Zero-Data Retention terms with all providers.
Google Workspace API
Direct OAuth 2.0 integration with Google Drive, Calendar, Meet, and Tasks. Streamline document import, export, and deadline scheduling securely.
Advanced Legal Drafting
Generates structured legal drafts (NDAs, commercial agreements, claims) with contextual risk evaluations, formatting, and inline statutory citations.
Technical Architecture Specifications
Detailed performance parameters and integration interfaces powering the Amicus model.
Security & Zero-Data Training Assurance
Legalica treats data privacy as a foundational requirement. Amicus v.3.1 executes within isolated, secure environments using transient in-memory storage. We do not harvest data, track cases, or train models on client interactions. All data is protected under GDPR and AES-256 encryption at rest, TLS 1.3 in transit. Read our complete Security Policy and Privacy Page.