AI document analysis you can check line by line
Ask for structured output with a location for every value — a table of field, value and the clause or page it came from. That turns document analysis into something you can audit in a minute instead of a paragraph you have to trust.
Document work is rarely 'what does this say'. It is 'what are the dates', 'how does this version differ' and 'which clause creates the obligation' — questions with checkable answers.
ChatOTL keeps the document and the questioning in one place: attach the file, ask in a thread, branch when a clause deserves its own investigation, and search your history later for what you found.
Ask for structure, with sources
- Request a table: field, value, and the clause or page number it came from.
- Ask explicitly what is missing or ambiguous rather than letting it guess.
- Ask for the three riskiest items and why each one is risky.
- Spot-check the values you will act on against the document itself.
Comparing two versions
Attach both versions in one message and ask for a change list grouped by materiality — what changes an obligation, what changes a number and what is only wording. Then check the material ones in the text.
How files reach the model
Attach up to 5 files per message at 15 MB each. Plain text, Markdown, CSV, JSON and source code are extracted and passed inline; PDFs and images are handed to the model through short-lived signed URLs. Files are scoped to your account by row-level security.
Keep the analysis reusable
Work one document per thread, branch for deep dives into a single clause, and use keyword search across your message history to find a previous extraction instead of redoing it.
Where it fits
Contract intake
Extract parties, term, notice periods and amounts with clause references.
Version diff
Attach both drafts and get a change list ordered by materiality.
Report triage
Pull the figures that moved and the explanation given for each.
Example prompts
- Extract every date, amount and party as a table with the clause number for each row.
- Compare these two versions. Group changes into material, numerical and cosmetic.
- What does this document leave ambiguous? List the questions I should ask before signing.
Limitations
- Scanned or low-quality images can be misread; verify values against the original page.
- No web browsing, so it cannot look up a referenced standard, filing or counterparty.
- Output is not legal, financial or compliance advice and always needs human review.
Frequently asked questions
Can it analyse scanned PDFs?
Images and PDFs are passed to the model, so legible scans usually work, but low-quality scans get misread. Always check extracted numbers against the page.
How do I trust an extraction?
Ask for the clause or page number alongside every value. An extraction with locations can be audited in a minute; one without cannot be checked at all.
Can I compare two contracts?
Yes — attach both in the same message and ask for the differences grouped by materiality rather than a flat diff.
Where are uploaded documents stored?
In private storage scoped to your account, with row-level security applied to every file, conversation and message you create.
Put one contract through it
Ask for a table with clause references and audit the rows.
Open ChatOTL