Investor Brief — Confidential

We turned legal procedure into a programmable system.

The Great Tribunal is a procedural reasoning engine that turns legal argument into a structured, enforceable process instead of an open-ended debate. Most legal tech tools generate content; we govern the flow of argument itself. We are raising to bring this arbitration pipeline to market.

2Distinct AI roles — magistrate & judge
3Production-ready codebases
0Direct competitors in this combination
$375B+Addressable training markets
▶ Hear a production now
The Problem

Why this matters

Legal disputes, compliance mediations, and professional training break down because no one clearly defines what must be proven, and by whom. Arguments drift into technical ambiguity, expert disagreement, and procedural confusion.

The Great Tribunal removes that ambiguity by defining proof upfront, enforcing it live, and preventing arguments from escaping into complexity.

The Core Technology

The arbitration engine — enforcing proof, not persuasion

The most defensible component of the platform is not the film production pipeline. It is the two-stage AI procedural governance system that no competitor has replicated. We didn't change the law; we changed how it's executed.

Stage 1 — Pre-Trial Magistrate
Calibrates the burden of proof before any argument begins

When a case creator submits their proposed burden of proof standard, the AI analyses it against common law principles and physical reality. If the standard is too low or manipulated, the AI rewrites it to be legally rigorous — specifying exactly what category of evidence is required. The calibrated standard is locked into the case record. Neither side can change it once the trial begins.

Stage 2 — AI Judge: Dynamic Burden Shift
Generates specific evidentiary standards at the exact moment extraordinary claims are made

During the proceeding, the AI monitors every player submission for extraordinary claims. When detected, the AI does not merely announce that the burden has shifted. It dynamically generates the specific evidentiary standard required to survive that particular claim. The player is locked into proving that standard. Rhetoric fails it. Only the named evidence survives.

Executive Perspectives

Ready-to-quote

"Courts rely on judges to manage the flow of argument. We've encoded that logic into the system itself."
"We didn't build a better argument engine. We built a system that forces arguments to resolve."
"This is what happens when you take courtroom procedure and make it computational."
Market Opportunity

Three independently large addressable markets

Legal Education & Professional Training
Law schools, bar preparation, continuing legal education. Unlimited AI-arbitrated practice sessions with AI-governed burden of proof, replacing expensive mock trial programmes.
$5B+ Global TAM
Corporate Training & Compliance
Ethics dilemmas and compliance scenarios. Every large organisation needs participatory training with an auditable documentary record of the procedural reasoning.
$370B+ Global TAM
Entertainment & Creator Economy
Consumer platform where creators produce and share governed trials on topics they care about — historical cases, philosophical debates, contemporary controversies.
$200B+ EdTech + Creator
Business Model

Three revenue streams at different growth curves

B2B SaaS
Enterprise & Education Licences
£499–£1,499 / month per organisation

Per-seat annual licences to law schools, corporate compliance teams, expert witness preparation firms. Predictable, high-retention, referral-driven.

Consumer
Premium Subscriptions
£9–£29 / month per user

Free tier with access to the platform. Premium unlocks longer productions, higher image quality, private cases, voice customisation.

API & Legal Tech
Arbitration Pipeline Access
Per-proceeding or volume licence

Third parties access the arbitration engine via API. The Dynamic Burden Shift system is independently licensable as a legal AI service.

Competitive Moat

Why this combination is hard to replicate

⚖️
Procedural governance system is the hardest part to build

Building a system that generates legally calibrated evidentiary standards for arbitrary real-time claims requires the full surrounding architecture: the initial calibration, real-time detection, and the inference engine. General-purpose LLMs cannot do this alone.

🔗
The combination, not any single part

AI video tools, debate platforms, mock trial software all exist independently. None has connected governed AI arbitration + structured narrative arc + dual visual rendering into a single pipeline.

🏛️
Verdict integrity creates institutional trust

The verdict evaluates whether the standard was met, not what the AI thinks sounds plausible. This epistemic integrity is what makes the platform credible for legal education and compliance.

The Ask

We are raising a seed round to connect the pipeline, launch the product, and close the first enterprise contracts. The technology is built. The raise is for execution, not exploration.

Raise Amount
[To be discussed]
Stage
Pre-seed / Seed
Use of Funds
System 3 engineering, go-to-market, first enterprise pilots
Time to First Revenue
6 months to first enterprise contract
▶ Hear the demo first
Resources

Explore the platform

This document is for discussion purposes only and does not constitute an offer of securities.