Architecture, broken down
Ask what a paper's system looks like and get the real components, pulled from its Architecture tab, not a generic summary.
Not a general chatbot. KXAI answers from the paper you have open, right now, architecture, results, gaps, equations, all cited back to the tab it came from. Open it from the button in the corner of any page, or try it below.
I'm KXAI. Ask me about papers, architectures, results, or how KinetixAI works. I'll cite my sources.
Demo mode — answers come from the papers in your catalog.
In your catalog
Profile data from ORCID. Works list limited to 8 most recent public entries.
Papers in your RAG catalog
Topic clusters
Full RAG ingestion (equations, code, tables) is a Scholar+ feature. See plans.
Ask what a paper's system looks like and get the real components, pulled from its Architecture tab, not a generic summary.
Ask for the key numbers and get the actual benchmark results, cited back to the Cheatsheet tab.
Ask what's missing or what to read next and get the paper's own stated limitations, plus the paper it leads to.
Ask for a way to remember it and get the paper's hook, built to actually stay with you.
Ask for the math or a definition and get it straight from the Cheatsheet, no hunting through the PDF.
Ask which paper in your bucket covers a topic, and KXAI searches all of them, then offers a one-click switch.
Ask the question you'd be embarrassed to ask in office hours, and get a cited answer from the actual paper instead of a half-remembered explanation.
Point a class at KXAI instead of forwarding a PDF with no way to check a claim, every answer cites the tab it came from.
Check whether your read of a paper's architecture or results is right, in seconds, cited back to the source, before it goes in a lit review.
Get the one detail you need before you ship, the actual mechanism or the actual number, not a confident guess.
Keep a whole literature review honest. Check a claim against the actual paper before it goes in a chapter, not after.
Point a whole lab or class at the same grounded assistant instead of everyone re-reading the same paper alone. Pairs with Campus and Teams plans.
KXAI runs in demo mode: every answer above is grounded in content we wrote for the papers in your bucket (Attention Is All You Need is free to try now, three more are in Paper Lab). Mapping an arbitrary paper of your own, the real headline capability, needs a backend that can read and understand any paper. That isn't live yet, so asking for it captures the request honestly, an email so we can notify you, instead of faking a result. The same box starts generating for real the day it ships, no rebuild needed.
KXAI's demo-mode Q&A is free on Explorer. Unlimited use across your whole bucket, plus your own Research RAG, is a Scholar feature.
Taste the whole platform.
Create accountFor serious self-study.
Go ScholarFor working practitioners who build and ship.
Go ProfessionalFull details on the pricing page.
It's already open on every page, free, no account needed for the demo papers.
I'm KXAI. Ask me about the papers in your bucket, their architecture, results or gaps, or ask me to map a paper of your own.
Map your own paper
Demo mode: answers come from the papers below. Mapping your own paper to 3D is a Scholar feature, coming soon. AI can make mistakes.