How is Vantage different from ChatGPT or Claude?

ChatGPT and Claude are great for one-off generation. Vantage is a full workspace. It connects your tools, tracks dependencies across projects, catches conflicts between products, and surfaces what needs your attention every morning. It also remembers every past decision, so a new PM can query across all projects and get cited answers in seconds.

Do I have to switch away from Notion or Linear?

No. You keep all your tools. Vantage connects to them and builds intelligence on top. When you're ready, you can push tickets to Linear or Jira. But the value starts before you create anything — just by connecting your tools and seeing what the intelligence layer surfaces.

What happens on day one?

You connect your tools — GitHub, Linear, Slack — 2 minutes each. Vantage indexes your existing data overnight. By the next morning, you see your first decision queue: what's stale, what conflicts, what changed. No manual setup. No templates to fill out.

What if I only manage one project?

Vantage works for single projects, but it shines when you manage 3–5 or more. Conflict detection, cross-project memory, and the decision queue are most valuable when you have multiple projects that need to stay in sync. If you manage one project, start with the free tier and see if the cited query engine alone saves you time.

All data encrypted in transit and at rest. We never train on your data — the AI providers we use are contractually barred from it. You can disconnect any integration or delete your account at any time. Pursuing SOC 2 Type II.

How does Vantage keep documents and tickets up to date?

When context shifts, you add the new information and Vantage rebuilds every connected deliverable. Documents, prototypes, and tickets all update. You review the changes, accept or reject each one, and approve. Nothing updates silently, and every change is traceable.

How do I get started?

Sign up free at app.vantageos.tech. Connect your tools, and generate your first grounded document within minutes. No credit card required. Upgrade when you need more projects or features.

Should feature requests be Jira Stories or Custom issue types?

A dedicated issue type "Feature Request" (configured in Jira > Issue Types) is cleaner than using Story — it allows different custom fields, workflows, and board configurations. If your Jira admin cannot create custom issue types, use Stories with a dedicated label.

How do I get sales and support to submit requests in Jira?

Sales and support teams often resist using Jira. Create a Jira Service Management project (if available) with a simple form or use an email-to-Jira automation: emails sent to feature-requests@yourcompany.com create Jira issues automatically. Lower the friction to zero for non-PM teams.

Is Jira good for feature request management?

Jira is capable but not purpose-built for feature request management. It lacks native vote aggregation by customer revenue and public community voting. For public customer-facing feedback, Canny is purpose-built. For internal stakeholder requests from sales and support, Jira works well.

How-To2026-08-219 min read

How to Track Feature Requests in Jira (Step-by-Step)

Jira's powerful custom field and project configuration system makes it capable of handling feature request tracking alongside standard engineering tickets. For teams fully committed to the Atlassian ecosystem, tracking feature requests in Jira avoids tool proliferation and keeps all product inputs in one searchable, reportable system.

This guide covers setting up a dedicated Jira project for feature request tracking with custom fields, prioritization views, and the workflow from request to epic.

Step-by-step guide

Create a Feature Requests project

In Jira, create a new project: Projects > Create Project > Scrum or Kanban (use Kanban for requests since they are not sprint-based). Name it "Feature Requests." Set the project key to "FR" for easy identification. Add the PM team and customer success as project members. Keep engineering as viewers only — feature requests are PM-owned, not engineering-owned.

Configure custom fields for requests

Go to Project Settings > Issue Types > Feature Request. Add custom fields: Customer Name (text), Customer ARR (number), Request Source (dropdown: Sales/Support/User Research/Internal), Business Justification (text area), and Votes (number — manually incremented). These fields enable MRR-weighted prioritization and source analysis.

Set up the request workflow

Configure a simple Kanban workflow for the project: New → Under Evaluation → Planned → In Progress → Done → Won't Fix. "Won't Fix" is an important terminal state — requests that are rejected need a clear final status with a decision rationale comment.

Create a triage filter

Create a Jira filter: project = "FR" AND status = "New" ORDER BY created DESC. Save it as "Feature Request Triage." Share this filter with the PM team. Use it in the weekly triage meeting to process new requests: review, assign source labels, fill in customer fields, and move to Under Evaluation or Won't Fix.

Build a prioritization dashboard

Create a Jira Dashboard with gadgets: Issue Statistics (requests by Customer ARR bucket), Two-Dimensional Filter Statistics (requests by status × source), and a Filter Results gadget showing top requests by Customer ARR. This dashboard gives a prioritization view without exporting to a spreadsheet.

Link requests to epics when prioritized

When a feature request reaches prioritization threshold, create a Jira Epic in the engineering project and link it to the feature request issue using the "Epic Link" or "Relates to" field. Add the Feature Request issue URL to the Epic description so the engineering team can trace the request back to the customer evidence.

Close the loop when features ship

When the linked Epic is marked Done, return to the Feature Request issue and transition it to Done. Add a comment: "This shipped in Sprint 42. Changelog: [URL]. Notified [customer-name] via customer success." This creates a closed loop from request → epic → shipped → customer notified, traceable in Jira.

Common mistakes

Mixing feature requests with engineering issues

Feature requests in the same project as engineering tickets get lost in sprint planning noise. A dedicated "FR" project with its own workflow keeps requests visible to PMs and invisible as sprint noise to engineers.

Not filling in Customer ARR on every request

If ARR data is missing on half the requests, the prioritization view is skewed. Make Customer ARR a required field in the Jira issue creation form for the FR project.

Using the Votes field inconsistently

The Jira Votes custom field (different from the built-in Jira vote system) requires manual updates. Create a Jira Automation rule to increment votes when someone adds a specific label or comment — this reduces the manual overhead.

Tips

Use Jira service management as the intake form for feature requests — it provides a customer-facing submission interface with structured fields

Create a Confluence page linking to the Feature Request dashboard for the executive team's monthly product review

Set a Jira Automation: "When a Feature Request reaches 5+ votes, notify the PM via email"

Export the top 20 feature requests monthly to a Confluence page as a "Voice of Customer" report for stakeholder alignment

How Vantage helps

Vantage integrates with Jira. When a Jira feature request is prioritized and an Epic is created, Vantage can generate the PRD and tickets for that Epic. Adding the feature request Jira issue as context ensures the customer problem language appears in the PRD rather than being rewritten from scratch by the PM.