TXYZ.AI

The core feature lets you upload a PDF or point TXYZ at a web page, then ask questions about the content. Answers come back with a document location reference, so you can check the claim against the original passage rather than trusting the summary blindly. The retrieval approach is built for research documents and handles both narrow, detailed questions and broad ones.

TXYZ Searching understands everyday phrasing, so you can describe what you need instead of assembling precise keywords. It leans on semantic understanding to return conceptually related work, even when it lacks your exact words, and it spans multiple disciplines, which helps when a topic crosses fields. Results come from an academic paper database kept current as new publications appear.

The writing side turns a research goal into a finished draft. You can auto-generate an outline from your references and AI conversations, then refine it with plain-language instructions. From there, TXYZ writes a full article using the information in your document, which suits researchers and content creators who need a coherent first draft without losing their own voice.

When you write, TXYZ proposes sources based on your content and context and adds them as citations. This keeps the referencing step inside the writing flow instead of sending you off to a separate tool, and it helps students and researchers hold to citation standards in papers and theses.

You can build your own AI agent for specific writing tasks using existing building blocks. A researcher might set up an agent tuned to academic writing in their subject, while another user creates one for a particular style. The point is a reusable assistant that fits your habits rather than a single general-purpose model.

TXYZ API connects your own app to the same AI engine. You upload PDFs by file or URL, chat with a bot that streams replies over SSE, and request suggested questions or document reference points. Credits drive the pricing, and the platform marks the session endpoints as free, with LLM calls costing one credit each. Teams have used it for medical research lookups, supply chain document analysis, and internal knowledge bases.

TXYZ states that uploaded papers stay private to the account holder and that deleting a private paper removes it from the database. Paid plans also carry a no-model-training commitment, meaning your interactions are not used to train the underlying models. The paid tiers support private sessions and bulk document uploads up to 300 pages on the Ultra plan.