KXAI

KXAI: your guide to the paper you're actually reading.

Not a general chatbot. KXAI answers from the paper you have open - architecture, results, gaps, equations - all cited back to the tab it came from. Try it on any demo paper, free, no account needed.

See KXAI in action

What makes KXAI different

KXAI is scoped to the paper in front of you. It reads the structured content KinetixAI extracts from each paper and answers from that - not from training data, not from a web search.

Grounded, not generative

Every answer cites the exact tab it came from. No confident guessing.

Paper-scoped by default

KXAI answers about the paper you have open, not general AI knowledge.

Honest when it doesn't know

If the answer isn't in the extracted content, it says so and captures your request.

What it actually does

Six things KXAI can do with the paper you have open. Try the example prompts directly.

01

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.

Try: What does this system actually look like?

02

Results you can check

Benchmark numbers get misremembered. Ask and get the exact figures cited back to the Cheatsheet tab.

Try: What were the actual benchmark numbers?

03

Gaps and what's next

The Limitations section is the most underread part of any paper. KXAI surfaces it on demand.

Try: What does this paper say it can't do?

04

A mnemonic that sticks

Built from the paper's core insight - something tied to what it actually does, not the title.

Try: Give me a way to remember what this paper does.

05

Equations and terms, on demand

Math-heavy papers mean constant scrolling. Ask for a definition and get it straight from the Cheatsheet.

Try: What is the softmax attention formula used here?

06

Cross-paper search

Once you have several papers, remembering which one covered a technique becomes the bottleneck. KXAI searches across all of them.

Try: Which paper in my bucket covers sparse attention?

Who it's for

Students

You don't understand the encoder-decoder attention mask and you're embarrassed to ask in class.

Ask KXAI. Get a cited answer from the Architecture tab, not a half-remembered explanation.

Teachers

You're assigning three papers and students will show up with misreadings.

Point the class at KXAI. Every answer cites its source - misreadings surface immediately.

Researchers

You need to check your read of a paper's architecture before it goes into your lit review.

Ask KXAI. Verify in seconds, cited back to the source, before it ships.

Professionals

You need the actual throughput numbers from a paper - not a blog post's summary of them.

Get the exact figures from the Results tab, with dataset and baseline named.

PhD students

You want to cite a paper's stated limitations but can't remember if you're paraphrasing correctly.

Ask KXAI what the paper says it can't do. Your citation is clean and you know it matches.

Labs & teams

Six researchers onboarding onto the same paper stack, everyone re-reading independently.

Point the whole team at KXAI. Consistent, cited answers. Pairs with Campus and Teams plans.

Honest about where this is

What's real today, and what's coming

Right now

Grounded Q&A on demo papers (Attention Is All You Need is free to try now)
Answers cited back to the Architecture, Cheatsheet, and Results tabs
Cross-paper search across your current bucket
Honest fallback with email capture when a paper isn't supported yet

Coming next

Arbitrary paper ingestion - upload or link any paper and KXAI reads it
Research RAG integration - KXAI answers across your full private library (PDFs, notes, repos)
Cross-paper reasoning - grounded answers synthesised across two or more papers in your RAG
Researcher catalog awareness - see which papers in your RAG are co-authored by the researcher you're reading

Asking KXAI about a paper outside the demo set captures your request honestly and notifies you when support ships. The same input box starts generating for real the day it goes live - no rebuild, no re-onboarding.

Common questions

Is this the same as asking ChatGPT about a paper? No. KXAI doesn't use training data to answer about papers. It uses the paper's own extracted content and cites every answer back to the tab it came from.

Can I use my own papers? Arbitrary paper support is coming. Enter a question about your paper - KXAI will capture your request and notify you when it ships.

What papers are in the demo bucket? Attention Is All You Need is free to try now. Three more are available in Paper Lab.

What happens when KXAI doesn't know something? It says so. No confident guessing. If the answer isn't in the extracted content, you get an honest response and your request is logged for when support improves.