Repetita Gravity

The description states that Repetita Gravity is:

• A general post-generation control process for long-form documents
• Demonstrated through a compact OpenAI Build Week application
• Designed to operate between AI-assisted drafting and final delivery
• Intended for use with documents such as legal submissions, technical specifications, research papers, business reports, emails, stories, and personal letters

The system treats recurring concepts as having "semantic mass" and uses a "Logical Gravity Centre" approach to determine where concepts should be consolidated.

Evidence The description states this is a "general post-generation control process for long-form documents"

Inference This appears to be an AI-powered document editing tool that operates after initial drafting but before final delivery

The description states:

• Repetita Gravity asks a "more consequential question" than typical repetition tools
• It focuses on semantic mass and logical centre rather than surface similarity
• The system is designed to preserve evidence, qualifications, exceptions, context, and distinctions that are often lost in traditional rewriting
• It treats every recurring concept as having semantic mass and moves content toward its "Logical Gravity Centre"
• The innovation is described as "loss-controlled semantic redistribution"

Evidence The description states these claims about the product's approach and innovation

Inference This represents a positioning shift from simple duplication detection to sophisticated semantic analysis and controlled consolidation

The description states:

• The problem affects "almost every kind of writing" including legal submissions, technical specifications, architecture documents, research papers, business reports, emails, stories, and personal letters
• It is intended for circumstances where reducing repetition is less important than proving nothing material was lost
• The methodology is relevant to legal, regulatory, compliance, policy, consulting, technical, academic, professional, creative, and personal writing

Evidence The description states these target use cases

Inference The product appears aimed at professionals who produce long-form documents where semantic accuracy is more important than brevity

Not evidenced.

The description does not contain any information about pricing, revenue model, monetization strategy, or business model.

The description states:

• Built with: css3, docker, github, gpt-5.6, html5, javascript, json-schema, open-ai-response-api, openai-codex, python
• Uses GPT-5.6 and Codex for bounded semantic decisions that cannot be established through lexical comparison alone
• Python performs deterministic reconciliation against the Conservation Ledger and the immutable original document
• The system evaluates document characteristics to determine processing approach:
  • Document length
  • Estimated token use
  • Section complexity
  • Number of recurrence families
  • Recurrence density
  • Dispersion across sections
  • Cross-family dependencies
  • Semantic risk

Evidence The description states these technical details and delivery approaches

Inference This suggests a sophisticated system with adaptive processing capabilities that can handle different document complexities

Not evidenced.

The description does not contain any information about:

• Revenue or ARR
• Customer base or adoption
• Product usage metrics
• Market traction
• Business development progress
• Any form of commercial activity beyond the hackathon submission

The description states:

• Repetita Gravity is substantially different from ProofRail, the author's other Build Week project
• ProofRail operates temporally across successive revisions and prevents accepted decisions from regressing
• Repetita Gravity operates spatially inside a single document and controls where recurring concepts receive their principal treatment
• It is not a grammar checker, paraphraser, summariser, or duplicate-word detector

Evidence The description states these distinctions from other tools

Inference This suggests the product addresses a specific gap in existing document editing tools, particularly those focused on repetition detection vs. semantic control

The description states:

• No original semantic unit may disappear silently
• Every claim, fact, item of evidence, qualification, limitation, exception, consequence, and recommendation must receive an explicit final disposition
• When available evidence does not justify automatic consolidation, Repetita Gravity fails closed
• The application remains conservative and exposes unresolved decisions instead of manufacturing certainty

Evidence The description states these safety mechanisms

Inference This suggests the system may be overly conservative in its approach, potentially limiting its utility for users seeking aggressive document reduction

1. What specific problems do you observe in current document writing and revision workflows that Repetita Gravity addresses?
2. How does your system handle edge cases where semantic meaning is ambiguous or context-dependent?
3. What evidence do you have that users actually need this level of semantic control over document consolidation?
4. How do you plan to validate the effectiveness of your "Logical Gravity Centre" approach in real-world use?
5. What are the practical limitations of your current implementation for large-scale document processing?
6. How does Repetita Gravity handle cross-document references and citations that might be affected by semantic redistribution?