Alegoria is a SaaS platform for technical content scripting for social media. It helps professionals and technical teams with the scripting of dense materials — such as standards, manuals, plans, or specifications — into playful and engaging journeys for social media.

The Alegoria methodology - intuitive and simple - generates Journeys structured into episodes that in turn give rise to complete scripts ready for production, with structured texts, audio and image suggestions, safeguards, and prompts serving as a base of production-ready artifacts for creating videos, podcasts, or posts.

Alegoria is a modern Artificial Intelligence tool. In addition to its main scripting function, it includes tools that enable observation of safeguards, regulatory risk analysis, content traceability, and full explainability of the scripting process, ensuring total human control over the generated content. Compliant with the Legal Framework for Artificial Intelligence, the National Policy on Plain Language, the General Data Protection Law, and the Fake News Law, it carries the concern of keeping, in human hands, total control over how Artificial Intelligence behaves to provide transparency, management, and compliance with Brazilian legislation.

Alegoria, ChatGPT, or Claude? #

Alegoria differentiates itself from platforms like ChatGPT or Claude by being a SaaS solution specialized in transforming technical documents into scripted journeys for social media, with knowledge graphs for traceability and regulatory compliance. More than that: The Alegoria Methodology handles the translation of documentation into narrative Journeys, structuring the strategy for presenting technical content by focusing on what is relevant and allowing the user to monitor and control the generated content.

Performance #

Here is the consolidation of results provided by Alegoria using the Answer Relevancy criterion, comparing to modern GPT (gpt-4.1-2025-04-14) and Claude (claude-sonnet-4-20250514) models in the Technical Document Scripting scenario.

1. Aggregated Results #

Total scenarios: 100
Criterion: winner = highest score in the line

2. Observations #

• Alegoria had the best overall performance, winning 45 out of 100 cases and maintaining the highest relevance average (0.943).
• Claude came in second place, with 35 wins and a competitive average (0.897), standing out in tasks where semantic precision dominates.
• GPT had 15 wins, but showed good consistency (0.83 average).
• In several lines, Alegoria and Claude tied with high scores (≥1.0), indicating parity in high semantic relevance.
• The variation between models suggests that Alegoria tends to be more robust in contextual consistency, maintaining scores close to the maximum in virtually all instances.

3. Conclusion #

Alegoria outperforms GPT and Claude in Answer Relevancy thanks to its GraphRAG implementation, which captures complex relationships between entities better than traditional vector RAG. This results in more precise and relevant contexts for the LLM to generate focused responses.

GraphRAG Advantages in Alegoria

GraphRAG builds knowledge graphs (nodes as entities, edges as relationships) from data, enabling retrieval via multi-hop reasoning — navigation through relational paths instead of simple semantic similarity.

• Greater contextual precision: Benchmarks show up to 35% higher accuracy in complex queries, with GraphRAG reaching 80-86% vs. 50% of the RAG baseline, aligning with Alegoria’s 0.943 average.
• Less noise and hallucinations: Filters relevant subgraphs, reducing “fuzzy context” and improving semantic relevance, as seen in Alegoria’s wins in 45/100 lines.
• Knowledge base + vectors integration: Combines vector searches (e.g., Qdrant) with Cypher queries for hybrid recall/precision, ideal for Alegoria’s technical scripts.

Why this explains Alegoria’s high performance

In Answer Relevancy (DeepEval/Confident AI), high scores depend on responses that strictly adhere to the query without deviations — Alegoria’s GraphRAG delivers this via hierarchical graphs and semantic clustering, surpassing GPT/Claude in consistency (average 0.943 vs. 0.834/0.897). Claude excels in point precision, but Alegoria wins in relational robustness for tasks like technical content generation.