Runs in turns
Claimant, defendant, judge and audit agents exchange arguments step by step.
⚖ Agentic AI courtroom preparation lab
Kernex Court Simulation
Court Simulation lets you test legal arguments in a realistic courtroom scenario before a hearing. It runs structured turns between claimant, defendant, judge and legal-audit agents, using your case materials, legal context, evidence map and procedure stage.
Test arguments Compare different ways to present the case.
Anticipate questions See how a judge may probe weak points.
Prepare strategy Identify missing proof, procedure risk and better options.
Future AI courtroom simulation
Simulation running
👤Claimant AgentBuilds the strongest supported argument from the case file.
🛡Defendant AgentTests defenses, contradictions and procedural objections.
📁Case Clerk AgentIndexes parties, claims, documents, dates and remedies.
🔍Evidence AuditorChecks whether each argument is supported by proof.
⚖AI Judge
Simulation
Core
Simulation
Core
?Likely questionsWhat will the judge ask first?
!Weak evidenceWhich point may collapse under scrutiny?
⏱Procedure riskDeadline, wrong forum or missing step.
✓Readiness reportStronger path, gaps and next preparation step.
This is a simulation environment. It does not decide the real case. It helps prepare the case by exposing strengths, weaknesses, likely questions, missing facts and procedural risk.
What the simulation does
The system recreates structured courtroom exchanges using controlled legal roles. Every agent is constrained by the uploaded case file, selected legal taxonomy, evidence map, procedure stage and verified legal context where available.
Tests legal positions
The simulation compares strong arguments, weak arguments and fallback approaches.
Questions the file
The judge agent probes missing facts, unclear documents and unsupported claims.
Produces readiness
The output is a preparation report, not a win/loss prediction.
Agentic courtroom architecture
The simulation is not one general chatbot. It is a controlled multi-agent legal preparation system where each agent performs a specific duty.
Case preparation agents
Case Clerk, Judgment Decomposition and Legal Context agents organize the file, extract issues and prepare the simulation record.
Adversarial agents
Claimant and Defendant agents test both sides so weak assumptions, contradictions and evidence gaps become visible.
Neutral review agents
Judge, Evidence Auditor, Procedure Risk and Bias Auditor agents check relevance, proof, fairness and procedural safety.
How each simulation runs
The workflow begins with the case file and ends with a structured readiness report. The user can review each turn to spot weak arguments, test alternatives and prepare strategy.
Turn-based exchange
Courtroom logic
1. Case fileDocuments, facts, parties, claims, dates, evidence, procedure stage and remedies are indexed.
2. Claimant turnThe claimant position is presented using supported facts and available evidence.
3. Defendant turnThe opposing side challenges evidence, procedure, credibility, assumptions and legal basis.
4. Judge turnThe judge agent asks neutral questions and identifies what remains unclear or unsupported.
5. Audit turnEvidence, procedure, precedent references and fairness are checked before a strategy report is produced.
Readiness intelligence
Preparation output
Strength mapWhere your position is strongest, moderate or weak.
Likely questionsQuestions a judge may ask at hearing or during case management.
Missing factsFacts the case needs but the file does not yet prove.
Evidence gapsDocuments, witnesses, certificates or records to obtain.
Next stepMediation, legal aid, lawyer review, court preparation, appeal, enforcement or protected referral.
LLM multiverse simulation
The multiverse is a disciplined comparison method. It runs several controlled versions of the courtroom exchange under different assumptions and then compares the results.
Tests the most persuasive version of the user’s argument and identifies what evidence must support it.
Reveals how the opposing side may challenge facts, documents, procedure or legal basis.
Checks what survives if the judge accepts only clearly supported facts and documents.
Tests deadline risk, wrong forum, missing procedural steps and admissibility problems.
Judgment reanalysis
When a judgment is uploaded, the system can decompose it into issues, facts found, evidence relied on, law applied, reasoning chain, remedy, contradictions and possible review questions. The reanalysis is record-grounded; it must label what is supported, missing, inferred or requiring lawyer review.
Issues decided
Identifies what the court actually decided and which claims were accepted or rejected.
Evidence relied on
Shows which documents, testimony, admissions or records the reasoning depends on.
Reasoning chain
Breaks the judgment into logic steps so contradictions or gaps can be reviewed.
Review questions
Prepares possible appeal, review, correction, enforcement or lawyer-review questions.
Governance and safe use
Court Simulation is a preparation tool. It does not replace the judge, court, lawyer, mediator or legal-aid officer. It must not invent facts or fake legal citations. Sensitive cases require protected handling and qualified human support.
Protected workspace
Confidential documents and sensitive facts must be handled only after login, consent, access control and audit logging.
Evidence-grounded output
Every argument should be marked as supported, inferred, missing, unsupported or requiring human review.
Human oversight
Lawyers, legal-aid officers, mediators or authorized reviewers should validate serious legal strategy outputs.