AI summarization that keeps what the decision depends on
Ask for a specific shape of summary, not a generic one. 'Decisions and owners', 'obligations and dates', 'the argument and its weakest step' and 'timeline of events' produce genuinely different, more useful output than 'summarise this document'.
A generic summary is a compression of everything, which means it drops precisely the detail you needed. Naming the shape up front is the difference between a paragraph you skim and one you act on.
ChatOTL handles the sources directly: attach the PDF, transcript, CSV or code file, then work the summary in the same thread until it is the right length and the right emphasis.
Pick the shape before you prompt
- Decisions and owners — for meeting transcripts and long threads.
- Obligations, dates and amounts — for contracts and statements of work.
- Argument and its weakest step — for papers, memos and proposals.
- Timeline of events — for incident reports and message histories.
- What changed since last version — when you paste both.
What you can summarise
PDFs, images, plain text, Markdown, CSV, JSON and source code, up to 5 files per message at 15 MB each. Text and code are extracted and passed inline; PDFs and images go to the model through short-lived signed URLs.
Tighten in the same thread
Do not restart with a better prompt. Ask for the same summary at half the length, or with one section expanded, so the model keeps the source and your earlier corrections in context. Branch if you need a second version for a different audience.
Check the load-bearing parts
Summaries are where quiet errors hide: a dropped negation, a rounded figure, an obligation attributed to the wrong party. Ask where each key point appears in the source and verify the ones a decision rests on.
Where it fits
Meeting transcript
Ask for decisions, owners and open questions — nothing else.
Contract skim
Extract obligations, dates and amounts, then verify each against the clause.
Long thread
Get the timeline and the current state before replying to any of it.
Example prompts
- From the attached transcript: decisions made, who owns each, and questions left open.
- List every obligation, date and amount in this contract with the clause number for each.
- Same summary, half the length, keeping every number.
Limitations
- No web browsing, so it cannot summarise a URL — attach or paste the content instead.
- Summaries can drop negations and misattribute claims; verify anything a decision depends on.
- Very long documents may need splitting across messages in the same thread.
Frequently asked questions
Can it summarise a web page from a link?
No. ChatOTL cannot browse the web. Paste the text or attach the file, and it will work from that.
How accurate are AI summaries?
Good enough for triage, not good enough for unverified reliance. The common failures are dropped qualifiers and misattributed statements, so check the points that carry a decision against the source.
What file types can I summarise?
PDFs, images, plain text, Markdown, CSV, JSON and source code — up to 5 files per message at 15 MB each.
Are summarised documents kept private?
Yes. Row-level security scopes every uploaded file, conversation and message to the account that created it.
Summarise the thing you have been avoiding
Name the shape you need and attach the file.
Open ChatOTL