Codex Predicta: The Psychohistory of Law
A big data platform that scrapes and analyzes public legal and corporate documents to predict future regulatory changes, litigation risks, and emerging market trends for niche industries.
Aura: The AI Authenticity Index
A Big Data project that scrapes public corporate data to generate an 'AI Authenticity Score', distinguishing genuine AI integration from superficial marketing hype for investors, job seekers, and strategists.
Inspired by the quest to distinguish human from replicant in 'Blade Runner' and the vast, hidden AI society of 'Hyperion's' TechnoCore, Aura is a Big Data platform designed to peer into the digital soul of a company. In today's market, every company claims to be 'AI-powered', creating a fog of hype. Aura cuts through this noise by acting as a 'digital Voight-Kampff test' for corporate AI.
Concept:
Aura continuously scrapes, aggregates, and analyzes a massive volume of publicly available data to build a multi-dimensional profile of a company's relationship with artificial intelligence. It doesn't just list tools; it measures the depth, maturity, and authenticity of AI integration across an entire organization. The final output is the 'Aura Score', a rating that signals whether a company's AI is a core part of its being or merely a superficial implant.
How It Works:
1. Data Ingestion (The Scrape): A distributed network of scrapers constantly gathers data from diverse sources, much like gathering disparate tales on a pilgrimage:
- Talent & HR: Job postings (analyzing seniority, team structure, specific skill requirements), employee profiles on professional networks (for aggregated skill density).
- Corporate Communications: Press releases, quarterly investor calls, annual reports, and marketing copy (to establish the public narrative).
- Technical Output: Engineering blogs, public GitHub repositories, research publications, and conference presentations (to find the ground truth).
- Product & Services: Product descriptions, user documentation, and case studies (to see how AI is actually productized).
2. Big Data Analysis (The Test): The collected data is processed through an analytical pipeline to generate key metrics:
- Integration Score: Using NLP to determine if AI is confined to a single 'AI Lab' or if its language and personnel are present across departments like product, marketing, and operations. A truly integrated AI is a pervasive TechnoCore, not a silo.
- Maturity Score: Differentiates between companies hiring junior staff for basic tasks versus those seeking Principal ML Engineers and publishing novel research. It looks for evidence of a mature, long-term AI strategy.
- Authenticity Gap: This is the core of the 'Voight-Kampff' test. It compares the grand, forward-looking statements from marketing and investor calls with the concrete technical evidence from engineering blogs and job requirements. A large gap between rhetoric and reality results in a low authenticity score, flagging potential 'AI-washing'.
3. The Aura Platform (The Verdict):
The results are presented on a subscription-based web platform. Users can search for companies and view their detailed 'Aura Profile'. This includes the overall Authenticity Score, a breakdown of individual metrics, a timeline of their AI journey, and a narrative summary that tells the story of their AI evolution. This service is highly valuable for:
- Venture Capitalists & Investors: To identify genuinely innovative companies and avoid overhyped investments.
- Tech Talent: To find companies with authentic, challenging AI work environments.
- B2B Leaders: For competitive analysis and to benchmark their own AI integration efforts.
Concept:
Aura continuously scrapes, aggregates, and analyzes a massive volume of publicly available data to build a multi-dimensional profile of a company's relationship with artificial intelligence. It doesn't just list tools; it measures the depth, maturity, and authenticity of AI integration across an entire organization. The final output is the 'Aura Score', a rating that signals whether a company's AI is a core part of its being or merely a superficial implant.
How It Works:
1. Data Ingestion (The Scrape): A distributed network of scrapers constantly gathers data from diverse sources, much like gathering disparate tales on a pilgrimage:
- Talent & HR: Job postings (analyzing seniority, team structure, specific skill requirements), employee profiles on professional networks (for aggregated skill density).
- Corporate Communications: Press releases, quarterly investor calls, annual reports, and marketing copy (to establish the public narrative).
- Technical Output: Engineering blogs, public GitHub repositories, research publications, and conference presentations (to find the ground truth).
- Product & Services: Product descriptions, user documentation, and case studies (to see how AI is actually productized).
2. Big Data Analysis (The Test): The collected data is processed through an analytical pipeline to generate key metrics:
- Integration Score: Using NLP to determine if AI is confined to a single 'AI Lab' or if its language and personnel are present across departments like product, marketing, and operations. A truly integrated AI is a pervasive TechnoCore, not a silo.
- Maturity Score: Differentiates between companies hiring junior staff for basic tasks versus those seeking Principal ML Engineers and publishing novel research. It looks for evidence of a mature, long-term AI strategy.
- Authenticity Gap: This is the core of the 'Voight-Kampff' test. It compares the grand, forward-looking statements from marketing and investor calls with the concrete technical evidence from engineering blogs and job requirements. A large gap between rhetoric and reality results in a low authenticity score, flagging potential 'AI-washing'.
3. The Aura Platform (The Verdict):
The results are presented on a subscription-based web platform. Users can search for companies and view their detailed 'Aura Profile'. This includes the overall Authenticity Score, a breakdown of individual metrics, a timeline of their AI journey, and a narrative summary that tells the story of their AI evolution. This service is highly valuable for:
- Venture Capitalists & Investors: To identify genuinely innovative companies and avoid overhyped investments.
- Tech Talent: To find companies with authentic, challenging AI work environments.
- B2B Leaders: For competitive analysis and to benchmark their own AI integration efforts.