Free AI user story generator
Paste the conversation. Get user stories back.
Drop in sprint planning notes, a refinement transcript, or the messy braindump you took during the call. The extraction engine reads it like a business analyst would and hands back user stories, bugs and tasks that trace to what people actually said. No prompt engineering, no account, no card.
0 / 12,000 characters
5 free runs per day. Nothing you paste is stored. The free tool returns titles, descriptions, priorities and labels; the deep fields belong to account holders.
Extraction, not invention
Why this generator starts from a conversation, not a prompt
Most AI user story generators are a thin wrapper on a chat model. You type "user stories for an export feature", it obliges with plausible fiction, and you spend the next hour deciding which parts your team actually meant. The stories look right and belong to nobody.
This one works the other way round. It reads a real conversation and extracts the stories that are already in it. When Maya says finance teams keep re-clicking a dead export button, that sentence becomes the story, and the story keeps the sentence. Nothing is invented to fill a template, and if the conversation contains a bug or a task rather than a story, it comes back labelled as what it is.
One thing to be straight about. The free tool on this page returns truncated items: title, description, priority, labels. Acceptance criteria, the INVEST assessment, dependencies and clarifying questions are locked behind a free account, and the locked rows in the results are exactly that, locked, not teased. The deep fields are the product. Showing you honestly where the free version ends beats pretending the preview is the whole thing.
The full output shape
What the same story looks like inside the product
Here is the export story from the sample transcript above, as a free account generates it. This is a curated demonstration of the real output shape, the same one the user stories artefact page documents in full.
Show export progress and notify when the file is ready
As a finance user exporting a report, I want visible confirmation that my export has started and a notification when it completes, so that I do not trigger the same export four times waiting for something to happen.
Acceptance criteria
- Given a finance user on the reports page, when they click Export, then the button enters a visible in-progress state within one second and cannot be clicked again.
- Given an export in progress, when the file finishes generating, then the user receives an email with a download link and the downloads drawer shows the file.
- Given an export that fails, when the job errors, then the in-progress state is replaced with a retry prompt and no email is sent.
INVEST assessment
- IIndependent of the CSV escaping fix, ships on its own.
- NThe email copy and drawer layout are open to negotiation with design.
- VKills the duplicate-export behaviour ops reported, valuable on day one.
- EFront-end state plus one email trigger, estimable without a spike.
- SSmall enough for one developer inside the sprint.
- TEach criterion above is a directly runnable test scenario.
Dependencies
- Email notification service must expose an export-complete trigger.
- Relates to the downloads drawer designs Priya is reviving in Figma.
Open questions
- Should the completion email go to the exporting user only, or to a configurable finance distribution list?
- How long do generated files stay downloadable? The retention policy Tom is writing should settle this before build.
"finance teams are exporting the same report four or five times because nothing confirms the export started" and "We need a visible in-progress state and an email when the file is ready"
Every field above is generated, including the open questions. When the meeting did not settle something, the story says so instead of guessing. The full anatomy of a good story lives in the user stories guide.
Two ways in
When to use this tool, and when to send the bot
Use this page when you already have text
The meeting happened, the notes exist, and you want stories out of them in the next two minutes. Paste, generate, done. It is also the fastest way to judge whether the extraction is any good before you commit to an account. Five runs a day, up to 12,000 characters each.
Use the meeting bot when the meeting has not happened yet
Paste a Zoom, Microsoft Teams or Google Meet link and Backlog.cloud joins the call, transcribes it, and has the full artefact set waiting when you hang up. It knows sprint planning from a retro and listens accordingly. You can also upload recordings, audio, or a photo of the whiteboard. The meeting to backlog page walks through that flow end to end.
Want to turn the entire meeting into a backlog?
Stories are one of 12 artefact types. The same conversation also carries bugs, tasks, decisions, action items and risks, and a free account extracts all of them, with acceptance criteria intact and a push to your work management platform at the end.
Create a free account3 free generations. No card.
FAQ
The free user story generator, answered
- Is this user story generator really free?
- Yes. 5 runs per IP per day, no account, no card, no email gate. The free tool returns story titles, descriptions, priorities and labels. A free account, also without a card, adds acceptance criteria, edge cases, dependencies and the other artefact types with 3 full generations included.
- What happens to the text I paste?
- It is sent to the extraction endpoint, used to produce the items you see, and not stored. There is no account attached to a free run, so there is nothing to store it against. If your notes contain something you would not put in an email, redact names before pasting, which is good practice with any online tool.
- Why are acceptance criteria locked in the free tool?
- Because the free endpoint physically cannot produce them. Its output format only contains title, description, type, priority and labels, so the deep fields are not generated and then hidden, they are never generated at all. The full story shape with Gherkin criteria, edge cases and dependencies is the product, and it comes with a free account rather than a public text box.
- How is this different from asking a chatbot to write user stories?
- A chatbot writes stories from a prompt, which means it invents whatever the prompt leaves out. This tool extracts stories from a conversation, so every item traces back to something a real person said. Inside the product that link is explicit, each story carries the verbatim quote it came from, and anything the meeting left ambiguous becomes a clarifying question instead of a confident guess.
- How many user stories will I get from one paste?
- As many as the text actually supports. A dense ten minutes of sprint planning might yield four or five items, a vague paragraph might yield one, and text with no extractable work yields none. The tool does not pad the list to look productive.
- Does it only generate user stories?
- The free tool returns stories, bugs and tasks, because a real conversation rarely contains only one kind of work. This page leads with stories, but if your notes describe a defect it will come back as a bug, not a story wearing a bug costume. The full product extends that to 12 artefact types.
- What kind of input works best?
- Real conversation. A transcript with speaker labels is ideal, raw meeting notes work well, and even a messy braindump is usable as long as it describes actual problems and requests. What works badly is a one-line prompt like "stories for a login page", because there is nothing to extract from it. That is chatbot territory, and this deliberately is not a chatbot.
Keep going
Related workflows and resources
User stories artefact
The full story format the product generates, field by field.
User stories guide
INVEST, Gherkin and the anatomy of a story a team can actually build.
Transcript to user stories
A worked transformation from raw transcript to sprint-ready stories.
Acceptance criteria generator
The companion tool for the Given/When/Then side of the story.
Meeting to Jira
How generated stories become real Jira issues, ADF and all.
Meeting to backlog
The wider workflow: one conversation, twelve artefact types.
Stop writing stories from memory
Send Backlog.cloud to your next planning call, or paste the transcript afterwards. Review the stories it grounds in real quotes, then push them to your work management platform.