Text Summarizer

What Text Summarizer helps you do

Condense long articles, meeting notes, or pasted documents into shorter key points. Treat the summary as a starting point — especially for technical, legal, or medical material where missing context can change the conclusion. It is most useful when you need a map of the source before reading it properly.

Your text is sent to Haivix AI endpoints to generate the summary. It is not stored as a permanent document archive on Haivix. Do not submit confidential, medical, legal, or regulated content.

How it works

Haivix uses an AI summarization endpoint. The model selects and rewrites important-looking sentences; it is not a deterministic extractive algorithm with fixed sentence scoring exposed in the UI. That means the output can change between runs, compress unevenly, or favor the opening of the document.

How to use Text Summarizer

1. Paste the full source text you want summarized, not just a fragment missing context.
2. Run Summarize and compare each bullet or paragraph against the original for missing caveats.
3. Check names, numbers, dates and decisions before acting on the summary.
4. Verify facts and conclusions against the source, then rewrite the recap in your own voice.
5. Summarize a section again with a narrower input if the result is too general.

When to use it

• Getting a quick overview of a long article you plan to read in full
• Drafting meeting notes recap from your own transcript
• Creating a first-pass abstract for internal research sharing
• Reducing a long thread to the decisions and open questions
• Preparing a short brief before a review call
• Checking whether a document covers the topics you expected

When not to use it

• Summarizing contracts, policies, or clinical guidance without expert review
• Replacing reading source material for safety-critical decisions
• Generating publishable summaries of news you have not verified
• Processing text you cannot send to a server-assisted AI service

Example

A 2,000-word product changelog might summarize to three themes (new API, deprecations, bug fixes). Check that deprecation dates and breaking changes were not dropped. If the summary says the old endpoint is removed next month, confirm the exact date and version in the source before announcing it.

What you can do with Text Summarizer

• Summarize a pasted article, transcript or set of notes.
• Reduce a long passage to a few key points.
• Create a first-pass abstract for internal sharing.
• Compare the summary with the source in one view.
• Iterate on a shorter section when the output loses detail.
• Copy the result into your notes for editing.

Example: recap a meeting transcript

Paste the transcript or notes in a coherent order. If the source has several unrelated sections, summarize them one at a time so the output does not blend decisions from different topics.

Check every bullet against the source. Look for dropped dates, owners, conditions and dissenting points, which are the details a summary is most likely to lose.

Rewrite the summary in your own words before sending it. A recap that reads well but assigns an action to the wrong person is worse than no recap.

What to know before you start

• Five free AI requests per day per browser.
• Summaries can omit exceptions, conditions, and minority viewpoints present in the source.
• Very long inputs may be truncated or summarized unevenly depending on model behavior.
• The summary does not verify facts or resolve contradictions inside the source.
• There is no citation tracking, so a claim cannot be traced to a paragraph automatically.

Common mistakes

• Treating AI summaries as complete or unbiased
• Summarizing text you do not have rights to process on a third-party service
• Using summaries in citations without reading the underlying source
• Assuming the first bullet is the most important point in the document
• Sending the summary as meeting minutes without checking who owns each action
• Summarizing a long document in one pass and missing a later exception
• Assuming a shorter summary is automatically better; a useful recap may need one more line for a condition or an owner

Troubleshooting

If the summary is too general, shorten the input to one section and run it again. A narrower source gives the model less room to average unrelated points.

If a key detail is missing, add it manually and check the surrounding claim. The summary is a draft, not an extraction guarantee.

If the output contradicts the source, treat the source as authoritative and discard the summary.

If the request fails, you may have reached the daily limit. The five requests are tracked locally per browser and reset the next day.

If two runs disagree, compare both against the source and keep the version that preserves the decisions and dates.

If the summary reads like a list of topics without any conclusion, add a short sentence naming the decision or next step yourself; the model does not know what your team intends to do with the document.