Someone joins your team and finds twelve presentations. A client sends a two-hundred-page manual due tomorrow. SazAI Corpus reads all of it once and hands back every document opened, in four formats.
What comes in, and what comes out
One file goes in, four formats come out
The presentation becomes one section per slide; the document, one per section; the spreadsheet, one per sheet; the PDF, one per page. Each section carries the image, the text and, when they exist, the speaker notes and the comments. The twelve presentations become twelve places you browse; the manual becomes two hundred sections you move through instead of reading.
The file knows more than the presentation showed: the slide someone hid appears for you, marked as hidden.
Your documents
One reading on entry, and everything it produced gets an address
An Office file is a package, and SazAI Corpus reads the whole package, once, through an engine that reads the format’s specification and does not interpret it. The X-ray is what comes out of that reading: the text with its origin, the comments with their state, the notes, the hidden items, the properties. And what the engine measured has a name; your editions enter as complete documents, and the comparison returns a number instead of an impression.
Every claim in the document gets an address, and the address belongs to the file, not to our opinion about it. The whole of it, with the receipt of what changed and what it does not prove, is in your documents.
Use cases
Where this solves something, and where it does not yet
Understanding material you did not produce. Comparing versions and knowing what changed. Translating a whole training program and being able to prove it arrived intact. Analyzing a portfolio instead of one file at a time.
The situations did not come from market research; they came from watching the same scene repeat across different sectors, and each one separates field testimony from the verifiable claim. The ones we have seen up close, together with what is not yet solved, are in use cases.
Neural network
Documents stop being a folder and become a diagram
Nothing sits loose in your vault. Every document is linked to its editions, every edition to its receipt, every comparison to both sides. The connectome is that diagram: every document a node, every link a synapse, and it grows with every upload without you assembling anything.
You move through it on screen. The agent moves through it from inside, node by node, with the origin and the measurement already sitting beside it, which is why the answer can come with its source. The whole network, and why its links are declared and never guessed, is in neural network.
The engine measures and does not opine. The one who interprets what was measured is the agent of SazAI Corpus, reading the same vault as you, with no source beyond your own.