About gentic.news
gentic.news is an AI-assisted news intelligence platform covering the AI ecosystem. Our editorial team uses AI tools to scan 48+ sources, extract insights, and publish structured intelligence — with human oversight on source selection, quality standards, and editorial direction.
Our Team
Ala Smith
Founder & Editor-in-Chief
Data engineer with expertise in AI systems, knowledge graphs, and large-scale data platforms. Responsible for editorial direction, source curation, quality standards, and system architecture. Reviews content quality, maintains classification rules, and oversees the editorial process.
AI Research Desk
AI-Assisted Content Production
Our AI systems handle high-volume content production: source scanning, entity extraction, sentiment analysis, and initial article drafting. All AI-generated content is clearly labeled and follows editorial guidelines set by the founding team. See our editorial process for full transparency.
Why This Exists
In early 2026, I was spending 2+ hours every morning just catching up on AI news — scrolling X, reading newsletters, checking ArXiv, monitoring HackerNews. Most of it was noise. The signal was buried.
So I built what I wished existed: an intelligence system that scans dozens of sources, extracts entities into a knowledge graph, detects patterns, makes verifiable predictions, and surfaces what actually matters — with my editorial oversight ensuring quality and accuracy.
No paywalls. No sponsored content. No "top 10 AI tools" listicles. Just structured intelligence from raw data, curated by someone who understands the AI landscape.
What Makes Us Different
We build a living knowledge graph that updates every 3 hours. Entity profiles, relationship maps, and trend detection — not just headlines.
We have data. Every article is scored for relevance and quality. Entities are extracted, linked, and tracked over time. Predictions are falsifiable and auto-verified.
We go deep on verticals: general AI news, Claude Code best practices, and retail AI — each with dedicated research and analysis pipelines.
AI-assisted production allows us to cover more ground than traditional newsrooms, while editorial oversight ensures accuracy and relevance. Every article is clearly labeled as AI-generated.
How It Works
- Source Curation — Our editor maintains a curated list of 48+ trusted sources including RSS feeds, X/Twitter accounts, and research repositories.
- AI-Assisted Filtering — A three-stage pipeline (keyword match, AI relevance scoring, duplicate detection) surfaces the most significant stories.
- Analysis & Extraction — Each article is scored for relevance, entities are extracted and linked into a knowledge graph, and sentiment is computed.
- Intelligence Layer — The knowledge graph powers entity profiles, relationship maps, competitive analysis, and weekly intelligence reports.
- Predictions — Signal detection and graph patterns feed a prediction engine that generates verifiable forecasts, with methodology and confidence levels disclosed.
- Editorial Review — Quality rules and source credibility standards are maintained by the editorial team. All content is labeled as AI-generated with links to our editorial process.
Metrics Glossary
How significant an article is to the AI landscape. Factors include topic importance, source authority, recency, and whether it represents a breakthrough.
Average tone of coverage about an entity. Positive (+0.3 to +1.0), neutral (-0.3 to +0.3), negative (-1.0 to -0.3).
Week-over-week change in mention frequency for an entity. Positive means growing coverage; negative means declining interest.
How likely a prediction is to come true, based on evidence strength. Very Likely (85-100%), Likely (70-84%), Possible (50-69%), Speculative (<50%).
Knowledge Graph
Every article is processed to extract entities — companies, people, AI models, technologies, and research topics. These entities are linked through relationships (developed, partnered, competes with, invested, etc.) and enriched with data from Wikipedia, Crunchbase, and arXiv.
The graph currently tracks 3,200+ entities with their relationships, timelines, and sentiment trends. It updates continuously as new articles are processed.
AI Transparency
AI-generated content: Article summaries, entity extraction, sentiment analysis, predictions, podcasts, and weekly intelligence reports are produced using AI tools. Every piece of AI-generated content is clearly labeled.
Human editorial oversight: Source selection, classification rules, quality standards, and system configuration are maintained by our editorial team. The founder reviews content quality, accuracy patterns, and prediction methodology.
Source attribution: Every article links to its original source. gentic.news does not claim original reporting — it aggregates, analyzes, and synthesizes published content with proper attribution.
Editorial process: For full details on how content is produced, verified, and published, see our editorial process page.
Contact
Questions, feedback, or partnership inquiries: contact@gentic.news
Follow us on X: @agent_ai_bot