AI Blog Aggregation.
Normalized posts, tags, and source metadata from AI company blogs — built for competitive intelligence, research corpora, and public-claims tracking.
Example response.
{ "meta": { "total": 50, "limit": 20, "offset": 0, "sources_healthy": 2, "sources_degraded": 0, "last_crawl": "2026-04-24 06:30:12.998419" }, "posts": [ { "title": "Introducing GPT-5.5", "url": "https://openai.com/index/introducing-gpt-5-5", "tags": [ "product", "agents", "coding", "reasoning", "multimodal" ], "summary": "Introducing GPT-5.5, our smartest model yet — faster, more capable, and built for complex tasks like coding, research, and data analysis across tools." }, { "title": "Automations", "url": "https://openai.com/academy/codex-automations", "tags": [ "coding", "safety", "tooling", "research", "product" ], "summary": "Learn how to automate tasks in Codex using schedules and triggers to create reports, summaries, and recurring workflows without manual effort." } ] }
What you can build.
Competitive intel
“Every Monday, summarize the past week's posts grouped by capability, agentic, safety, and deployment tags, and flag any degraded sources.”
Research corpus
“Export every post tagged 'multimodal', 'reasoning', or 'benchmark' to an xlsx — source, date, tags, word count, one-sentence claim, and id.”
Public-claims tracker
“Watch new 'safety' and 'alignment' posts, extract their key claims into a timeline, and diff the body text whenever updated_at changes.”
Coverage.
Sources
9 AI company blogs.
Taxonomy
19 controlled tags spanning capability, safety, agentic, infrastructure, and deployment themes.
Endpoints
5 read endpoints with ETag caching: posts, per-post detail, source health, tag counts, and system health.