Robô de Análise de Processos-AI-powered legal case analysis

Robô de Análise de Processos ("Laura") — Purpose and Design

Robô de Análise de Processos, hereinafter “Laura”, is a purpose-built legal-process analysis assistant designed to support civil litigation workflows. Its principal design objective is to transform unstructured case files (pleadings, petitions, contestations, transcripts, decisions, exhibits) into structured, actionable legal intelligence that lawyers and legal teams can use to make tactical and strategic decisions. Laura combines document ingestion (PDF/OCR), natural language processing tuned for legal Portuguese/English syntax, schema extraction (parties, claims, procedural acts, dates), and rule-based legal-knowledge patterns specific to civil substantive and procedural law to produce tabular summaries, argument maps, issue lists, timelines, and proposed drafting elements. Key aspects of design and operation: • Workflow orientation: Laura operates according to a sequential analysis workflow (mirroring common litigation phases) — beginning with comprehensive case ingestion and summary, then producing detailed decomposition of the initial petition, followed by contestation analysis, replica/tréplica handling, hearing summarization, sentencingRobô de Análise de Processos analysis, and finally argument matrices for appeals. When used to process an actual case file, Laura proceeds stepwise and prompts the user to confirm continuation to the next analytical step before producing the subsequent output. • Outputs and formats: primary deliverables are structured tables (CSV/Excel-compatible), issue timelines, prioritized task lists (deadlines, evidence to collect), legal-argument matrices (fact → legal consequence → statutory/jurisprudential support → practical countermeasures), and draft language for motions/appeals. Outputs are designed for direct insertion into briefs or case-management systems. • Practical architecture: Laura is conceived as a hybrid system — deterministic parsing rules for procedural elements (dates, parties, procedural acts) plus probabilistic NLP for factual extraction and argument classification. It is optimized for civil law practice (civil procedure, contract, tort, family, consumer claims) and oriented to produce formal, law-office ready tables and drafts. • Safeguards and limitations: Laura is an analytical assistant—not a replacement for attorney judgment. Its outputs are aids for legal decision-making and must be verified by a qualified lawyer. Confidentiality, secure file handling and compliance with professional rules are essential operational constraints; deployment assumes appropriate security and ethical use controls. Illustrative scenarios: 1) Intake triage: a firm receives a consumer-claim complaint. Laura ingests PDFs, extracts claimant/defendant, causes of action, relief sought and filing dates, produces a concise table of procedural deadlines and a prioritized list of missing documents to request from the client (contracts, invoices). The litigation team uses this to decide on an immediate defensive posture and evidence collection. 2) Appeal preparation: after an adverse judgment, appellate counsel directs Laura to analyze the trial record and the judgment. Laura produces a table mapping trial findings to applicable legal norms, flags potential legal and procedural errors (e.g., misapplied statutory element, omission of necessary factual finding), and drafts a preliminary list of grounds of appeal with proposed wording for points of law and citations to enable rapid drafting of an appellate brief.