AI agents for Fullstory
A Monmo agent works with Fullstory like a product analyst who has time to watch the replays. It finds the sessions behind a drop in a funnel, writes up what people actually did, reports rage clicks and error clicks each week, and turns a customer's complaint into steps an engineer can reproduce. It uses your own Fullstory access and asks before it saves or changes anything.
Updated 2026-11-13 · Free to start. Paid plans from $15 a month.
What agents do in Fullstory
Watch the sessions behind a funnel drop
When checkout completion falls, it finds sessions that reached the payment step and left, plays a sample in its own browser, and writes what went wrong with a link to each moment.
AskCheckout completion fell this week. Watch 20 sessions that left at the payment step and tell me why.
Report frustration every Monday
Every Monday it ranks the pages with the most rage clicks, dead clicks and error clicks, compares them with the week before and attaches two example sessions for each.
AskEvery Monday at 9, list the five pages with the most rage and error clicks, with example sessions.
Turn a ticket into a reproduction
From a Zendesk ticket it finds the customer's session, notes the steps, the console errors and the browser, and drafts a Jira issue. Creating the issue waits for your approval.
AskFind the session behind ticket 48213, write reproduction steps and draft a Jira bug for the web team.
Define a segment
Describe the people you care about, such as visitors who added to cart but did not buy within seven days, and it builds the segment, checks the count looks right and asks before saving it.
AskBuild a segment of trial users who opened Settings three times but never invited a teammate.
Compare before and after a release
After a release it compares error clicks, conversion and time on the changed page for the week before and after, and tells you whether the change helped, hurt or made no clear difference.
AskWe shipped the new pricing page on Tuesday. Compare conversion and error clicks before and after.
Check what recordings capture
It reviews recent sessions for form fields or text that show personal details which should be masked, and lists the elements to exclude. Changing privacy settings stays your decision.
AskReview last week's sessions on the account pages and list any personal details that should be masked.
Brief the team on a feature
It counts who used a feature, how often and where they got stuck, watches a handful of sessions and writes a one-page note in Notion for the next planning meeting.
AskWrite a one-page note on how people used the new export button in its first month.
How it connects
- 1You connect your own Fullstory account once, with your sign-in or an API key. An administrator in your Fullstory organisation may need to create the key or approve the connection.
- 2You choose which agents may use Fullstory. A product, engineering or support agent benefits from it; a finance agent has no reason to watch sessions.
- 3Searching sessions, watching replays and writing up findings need no approval. Saving a segment, adding notes, changing privacy or capture settings, and creating issues in other apps ask first.
More in Analytics and data
Other apps of this kind that agents work in, each with its own page.
Questions people ask
Can an AI agent watch Fullstory session replays for me?
Yes. A Monmo AI agent opens the replays in its own browser, watches the sessions you point it at or a sample from a segment, and writes up what people did and where they struggled, with a link to each moment. You can watch its screen while it works and ask it to look again at any session.
Will connecting Fullstory give the agent access to customer data?
It sees what your Fullstory account sees, and no more. Fields your Fullstory settings mask or exclude are never captured, so the agent cannot see them either. It quotes what it needs for a finding and links to the session rather than copying personal details into reports.
Can it turn a Fullstory session into a bug report?
Yes, that is one of its most useful jobs. From a ticket or a customer email it finds the matching session, writes numbered reproduction steps with the console errors and browser details, and drafts the issue in Jira, Linear or GitHub. The issue is created only after you allow it.
Can an AI agent find out why users drop out of a funnel?
It can show you what happened, which is usually most of the answer. It finds sessions that left at the step in question, watches a sample, groups what it sees, such as a hidden button or an error on submit, and gives each pattern a count and example sessions. Deciding what to change stays with you.