Import epics directly from Jira, GitHub, GitLab, or Azure DevOps — or describe a feature from scratch. Storymate's AI generates structured, INVEST-compliant user stories with acceptance criteria, ready to review and push straight back to your tools.
Refinement meetings run long. Quality varies. Acceptance criteria are forgotten. Storymate eliminates the grunt work so your team can focus on building.
From feature description to approved stories, test cases, sprint plans, and backlog push — Storymate handles it all.
Connect to Jira, GitHub, GitLab, or Azure DevOps and pull epics directly into Storymate with one click. No copy-paste, no reformatting — your existing backlog becomes the starting point for AI slicing immediately.
Paste a feature description and let the LLM decompose it into INVEST-compliant user stories with acceptance criteria in seconds. Extend anytime with "add more stories."
Generate structured test cases from approved stories using AI. Review, approve, or reject individually, then push to TestRail, Xray, or ZephyrScale.
Generate AI-suggested sprint allocations from approved stories with a drag-and-drop editor. Set per-sprint capacities, auto-fill from historical velocity data, save named plans, and export directly to GitHub, GitLab, Jira, or Azure DevOps.
Let the AI improve a rough feature description before slicing — clearer input, better stories. Duplicate story detection flags redundant output automatically.
Define user personas that guide how the AI frames stories. Stories are generated with the right "As a…" voice for each type of user in your system.
Connect your own AI backend — Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic, or any OpenAI-compatible endpoint. Full control over model and cost.
Approve, modify, or reject each story or test case individually. Full inline editing with revision history. Nothing reaches your backlog without explicit sign-off.
A visual matrix linking features → stories → test cases with coverage stats. Export to CSV for audits, compliance, or stakeholder reporting.
Define when a story is ready to sprint — use the guided six-question wizard, write your own criteria with AI refinement, or extract them from a Confluence page or uploaded document. Configurable rules (Blocking or Warning) validate every story automatically during review.
Define reusable prompts embedding your team's language, domain rules, and story format. Separate prompt libraries for stories and test cases.
Upload specs, business test cases, or organigrams as slicing context. Pull documents automatically from Confluence wikis via connector sync.
Export stories to Markdown or CSV, test cases to CSV or JSON. Share a feature's stories via a time-limited public HTML link — no account required for viewers.
A guided nine-step wizard walks new projects through documentation sources, estimation methodology, sprint defaults, Definition of Ready, domain context prompt, and connector setup — all optional, all editable later.
Enterprise-grade single sign-on via SAML 2.0. Integrate with your identity provider — Okta, Entra ID, or any SAML-compatible IdP.
Full audit trail of all org actions for compliance and security reviews. Machine API keys for CI/CD integration. Outbound webhooks to Slack, Teams, or any HTTP endpoint.
By connecting your own LLM endpoint, your organisation retains full sovereignty over where AI workloads are executed and where inference-time data flows. Apply your existing security controls — DLP policies, anomaly detection, and traffic inspection — directly at the inferencing layer. Leverage your organisation's commercial agreements and preferential pricing arrangements with any LLM provider, and maintain complete visibility and governance over your AI expenditure without vendor lock-in.
The nine-step project wizard configures your DoR, estimation method, sprint defaults, and connectors in one go. Then import an existing epic from Jira, GitHub, GitLab, or Azure DevOps — or write a plain-language description from scratch. Attach domain documents and choose a prompt template to guide the AI's style.
Storymate returns structured user stories with acceptance criteria. Approve as-is, modify the text, or reject stories that miss the mark.
Assign approved stories to sprint plans, then push them directly to GitHub, GitLab, Jira, or ADO — no copy-paste, no reformatting.
Push stories and test cases, pull epics and documents — Storymate connects to every tool your team already relies on.
Real feedback from product teams that replaced hours of refinement with Storymate.
"We cut our refinement meeting time by 60% in the first sprint. The AI-generated acceptance criteria are surprisingly accurate — we rarely need to modify them."
"The custom prompt templates are a game-changer. We embedded our domain vocabulary and readiness rules once, and now every story comes out perfectly formatted."
"We plugged in our Azure OpenAI deployment in minutes. All traffic stays within our tenant, our existing spend commitments apply, and our security team can monitor inference calls the same way they monitor any other API."
Pay only for what your team uses. Switch between monthly and annual billing anytime.
One project. Perfect for individual PMs getting started with AI story slicing.
One power project with prompts, documents, and test case management.
Unlimited projects, full feature access, and dedicated support for your team.
| Feature | Solo Basic | Solo Pro | Business |
|---|---|---|---|
| Concurrent projects | 1 | 1 | Unlimited |
| AI story slicing | ✓ | ✓ | ✓ |
| Connectors | ✓ | ✓ | ✓ |
| Custom prompt templates | — | ✓ | ✓ |
| Reference documents | — | ✓ | ✓ |
| Test case management | — | ✓ | ✓ |
| API access | — | — | ✓ |
| Audit logs | — | — | ✓ |
| SAML / SSO | — | — | ✓ |
All plans include core story slicing. Need a custom plan? Contact us
Built for enterprise teams that demand full control over their AI stack and data pipeline. Get in touch to see Storymate in action.