AI web agent re-sync schedules: keeping answers current as your site changes

Introduction

A team changes its refund window from 30 days to 14 days at 4pm. The page is correct. The chatbot still quotes 30 days at 4:05.

Matram had processed the earlier page, and the next scheduled crawl had not run. That gap is harmless for routine copy. For a price, policy or product limit, it is a customer problem.

This is what an AI chatbot auto re-crawl is meant to manage. Matram revisits connected sources on a plan-based schedule and processes the current material for later answers. The useful part is not simply that a crawler runs. It is knowing when the schedule is enough, when to intervene and how to prove that the revised answer is ready.

What changes when Matram re-crawls a source

Matram does not open the public website from scratch every time a visitor asks something. It fetches approved sources, splits their content into passages, indexes those passages and retrieves the closest ones when forming an answer. The reply includes a link to the page it used.

When Matram re-crawls a website or connected help centre, it revisits that source and processes the content available at that point. The next relevant question can then draw from the revised passages.

Problems start when two versions remain connected. A new pricing page may disagree with an old PDF. The crawler cannot know which one the business meant to retire. It can only process what the team left available.

An AI chatbot auto re-crawl keeps the index moving. Content ownership keeps it trustworthy.

Matram’s schedule is plan-based, not immediate

Matram’s current features page states that scheduled auto-sync runs daily, weekly or monthly by plan. The relevant interval is the one attached to the active workspace and source.

That means two things in practice.

First, do not promise an immediate Matram update. The page may be live while the agent still uses the previous indexed copy.

Second, do not assume every workspace refreshes daily. Check the plan and source status before setting an internal service level around content freshness.

For most educational pages, the normal schedule is fine. Nobody is harmed if a new blog post becomes answerable later that day or later that week. A changed cancellation rule is different. Waiting for the routine AI chatbot auto re-crawl leaves a period in which the website and the answer can disagree.

Decide from the cost of a stale answer

The fastest way to choose a refresh action is to ask one question: what happens if Matram gives yesterday’s answer today?

This is an operating rule for the content team, not a claim that Matram assigns those priorities itself. The AI chatbot auto re-crawl discovers source changes. Your team decides which changes cannot wait.

Use one release path for important updates

A reliable Matram update should follow the same order every time. Keeping the process boring is a strength here.

1. Change the source Matram is meant to trust

Publish the final approved version first. Remove or clearly retire any page or file that states the old fact. If the same policy exists in three places, fix all three or reduce them to one canonical page.

This is the part teams often skip. They refresh Matram perfectly, then discover that the crawler faithfully indexed two contradictory answers.

The rule-based versus AI chatbot guide explains the difference. A generated agent can answer many phrasings without a separate branch for each one, but the freedom comes from reading source material. Confused material still produces confused retrieval.

2. Choose scheduled or manual refresh

Low-risk copy can wait for the plan’s schedule. For a material change, use the re-sync control that Matram exposes for that source.

Matram specifically documents manual re-sync for Zendesk Help Center content after new articles are published. For another connector or source type, use the action visible in the current workspace rather than assuming the Zendesk control exists everywhere.

3. Wait for Matram to finish processing

Adding a source through Matram’s API queues ingestion in the background. Matram notes that a large site can take minutes to finish. A test made while the source is still processing is not a valid test of the update.

Wait for the chatbot to return to a ready state. Then start a fresh test conversation so an earlier exchange does not muddy the result.

4. Ask the uncomfortable version of the question

Do not test only the sentence copied from the new page. Ask how a customer would ask it, then ask the edge case.

If a refund window changed, try:

• “How long do I have to return this?”
• “Can I return it after 20 days?”
• “Does the same rule apply to sale items?”
• “I thought the limit was 30 days. Is that still true?”

Open the source link below each answer. If Matram gives the right number from the wrong page, the source set still needs work.

5. Record what passed

Keep a short release note: source changed, person responsible, refresh method, completion time, test questions and result. This is enough to trace the next stale answer without building a content-governance bureaucracy around a five-minute check.

A completed crawl can still leave a bad answer

A green status is useful, but it is not editorial approval. Three failures can survive a successful AI chatbot auto re-crawl.

The old fact still exists elsewhere. Matram retrieves relevant passages, and an archived page may still look relevant.

The new wording is vague. “Selected plans include priority support” does not tell the agent which plans qualify.

The scope is missing. A delivery promise may apply to one country while the page reads as if it applies everywhere.

Matram’s citations make each problem easier to trace. Strict mode can also keep an answer inside approved material and refuse when the source does not cover the question. Neither feature can turn an ambiguous sentence into a clear policy.

The chatbot best-practices guide recommends testing important questions again after a content change. Treat that as part of publishing, not as cleanup after a customer spots the problem.

Treat uploaded files differently from live pages

A public URL can be crawled again. A PDF edited on somebody’s laptop cannot.

If Matram holds an uploaded PDF or DOCX and the approved document changes, replace or reprocess the file through the supported workflow. Do not wait for AI chatbot auto re-crawl to discover a local file it cannot see.

Sitemaps have their own simple check. Confirm that new pages appear in the sitemap and retired URLs no longer do. A correct schedule cannot fetch a URL the sitemap never exposes.

When a page is deleted, verify that Matram no longer cites it and that a current source covers the questions visitors will continue to ask. A redirect helps people reach the replacement page, but it should not be treated as proof that every stored passage has disappeared.

Watch the conversations, not only the source list

Stale content often shows itself in ordinary language before it shows up in a dashboard warning. Visitors mention the old plan name. A support agent notices that the bot still says “30 days”. A citation opens a page that the website navigation no longer uses.

Give one person ownership of those signals. Their routine can stay short:

• scan recent Matram conversations for retired names and figures;
• review unanswered and escalated questions;
• retest high-risk facts after every related release;
• confirm that citations open current pages;
• remove duplicate or obsolete sources; and
• check that connected sources still authenticate and sync.

This is where AI chatbot auto re-crawl becomes part of publishing rather than an invisible technical feature. The crawler handles repetition. A person still decides whether the result is fit to show a customer.

The chatbot versus live chat guide is useful for the other boundary: even a perfectly current source cannot replace human judgement in a complaint, negotiation or account-specific decision.

Frequently asked questions

How often does Matram re-crawl content?

Matram states that scheduled auto-sync runs daily, weekly or monthly by plan. Check the interval attached to the current workspace rather than assuming every source refreshes daily.

Can Matram refresh a Zendesk Help Center manually?

Yes. Matram’s Zendesk integration page says a team can trigger a manual re-sync after publishing new Help Center articles.

Will an AI chatbot auto re-crawl update an uploaded PDF?

Do not rely on it. Replace or reprocess the uploaded file when the approved document changes outside Matram.

How do I know the new answer is ready?

Wait for processing to finish, start a fresh conversation, ask several versions of the affected question and open the citation under each answer.

Does every website edit need a manual re-sync?

No. Let the schedule handle low-risk copy. Act sooner when a stale answer could change a customer’s purchase, eligibility, rights or next step.

Make the content check part of publishing

An AI chatbot auto re-crawl solves the repetitive part of keeping Matram current. It does not know which change is urgent, which old page should be retired or whether the new wording answers the question people actually ask.

Use the scheduled sync for routine updates. For a material change, publish one authoritative source, refresh it through the available Matram control, wait for processing and test the real question plus its edge cases. Finish by opening the citation.

Start a 30-day Matram trial with no credit card. Connect a real source, change one page and run the full publish, re-sync and test cycle before using it on customer-facing content.