The full gallery
Tech stack
60 projects
Compare and evaluate AI models across coding, reasoning, agents, and other benchmarks.
davidtsong · HN
Benchmarklist: track AI benchmarks (2.4k+), models, and capabilities
Free AI assessment that identifies learning strengths and gaps, recommending personalized Khan Academy lessons.
@edsull · X
My vibe coding team of agents set up a series of AI assessments for each subject and each grade level. Check it out!
Discover and track AI industry stocks with US/A-share mapping and one-click portfolio deployment.
yaoleifly · GitHub
ai-stock-pool AI industry-chain stock pool with US/A-share mapping, active discovery, policy pressure, and one-click deployment.
Scan websites for AI usage and test chatbots for bias and safety with this open-source EU AI Act compliance toolkit.
@sebuzdugan · X
building @getfrai , an open source toolkit that helps ML engineers navigate EU AI Act compliance, model cards, risk files, the boring but necessary stuff
View global AI tool adoption trends, search preferences by country, and track SDK downloads daily.
pixipace · HN
Who is using AI? A daily tracker, 1,600+ city heatmap, DOI dataset
Get AI-powered investment research tools like DCF models and stock screening for individual investors.
@StephanInvests · X
Building a financial saas at the lowest price for people to put more towards their financial goals
AI platform to ask questions, generate images, and speak hands-free for better decision-making.
@Akinzoooo · X
Track AI industry trends and intelligence with evidence-backed data updates.
barretlee · GitHub
agent-pulse Evidence-backed AI industry intelligence — trends, source updates, daily data refreshes, and weekly decision briefs.
View and compare public opinions and benchmark ratings for leading AI models.
u/TasteMysterious5285 · Reddit
I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi
Autonomous AI system that identifies high-value SEO ranking opportunities and executes optimizations automatically.
@hola_gmi · X
built with claude ai. —
Discover and validate AI product opportunities using customer pain points, competitive signals, and market data.
vinitk80555 · HN
AI Product Opportunity
20 buyer-style prompts × 5 AI engines = 100 observation points per audit. Score 0-100. Free 60-second scan. Crypto-native methodology, every weight published.
@citeOS_io · X
is all yours
