Features

As a user I want to manage my projects integration with Leanmote

As a user, I want to create and save a custom view from my selected filters, so that I can easily return to it later and the system can use the context to personalize recommendations or train the agent for me. Acceptance Criteria Trigger Creation Pop-up When I click "Save View" after applying filters, a pop-up appears. Pop-up Fields Name of View (required): text field to give the view a recognizable name. Context (optional): a free-text field where I can describe the purpose of the view (used to train the agent later for personalized insights). Editing After creation, I can edit both the Name and Context of the saved view. Saving & Access Saved views appear in my list of views and can be selected/applied directly. Persistence Saved views are tied to my user account so I can access them on subsequent sessions.

Feature Request: Add Pick Up Time in Review Collaboration Summary Introduce a unified Pick Up Time metric that captures the time from PR submission to the first reviewer interaction (comment, approval, or rejection). This will replace the current split metrics (“First Comment” and “Time to Approval”) as the primary measure of the initial touchpoint. Problem / Motivation Today, responsiveness in review collaboration is measured in two ways: First Comment Time → time until a reviewer leaves a comment. Time to Approval → time until a reviewer approves the PR. However, this split doesn’t fully reflect the first touchpoint between submitter and reviewer, since the reviewer’s first action could be either a comment, an approval, or a rejection. Teams lack a holistic view of when a PR is actually “picked up” for the first time. Proposed Solution Introduce a Pick Up Time metric defined as the time from PR submission to the first reviewer action of any type (comment, approval, or rejection). Display Pick Up Time alongside existing review metrics in dashboards. Maintain the ability to drill down into “First Comment Time” and “Time to Approval” separately for more detailed analysis. Expected Benefits Provides a single, clear indicator of review responsiveness. Reduces ambiguity about what counts as the “first response.” Helps identify bottlenecks earlier in the review workflow. Complements existing metrics by giving both a holistic view (Pick Up Time) and detailed views (comment vs approval).

Some organisations need to calculate costs or other KPIs using custom attributes (e.g., customer segmentation, labels, or priority levels). To support this, we are introducing Custom Fields Mapping: Create & Map Custom Fields Users will be able to define their own custom fields in Leanmote and map them directly to existing custom fields in Jira (first supported tool, with others to follow). Example: Map “Labels”, “Customers”, or “Priority” in Jira to custom fields in Leanmote for richer analysis. Enhanced Filtering & Analysis Once mapped, these fields will automatically appear in filters and reports, enabling deeper analysis and more tailored KPIs. Example: Filter delivery metrics by customer, compare performance by priority level, or analyze outcomes across different labels. Phased Rollout Phase 1 (Early Access): Configuration available via Customer Success team for onboarding and setup. Phase 2 (Self-Service): Full management through our Admin Console, giving customers direct control over creating, editing, and mapping their fields.

We’re introducing a new Flow Efficiency breakdown by issue type (e.g., Task, Bug, Story, Improvement) to help teams understand where their time and effort are being invested — and whether technical debt is consuming too much capacity. Key Capabilities: Efficiency by Issue Type: Analyze flow efficiency separately for Bugs, Tasks, Stories, and other custom issue types. Technical Debt Awareness: Identify trends such as excessive time spent on bugs or rework, highlighting technical debt accumulation over time. Effort Investment Insights: Visualize how engineering time is split across planned work vs. unplanned fixes or support tasks. Use Cases: Detect if reactive work (bugs, support) is slowing down feature delivery Justify refactoring or tech debt reduction efforts Improve planning balance between innovation and maintenance User Value: Empowers engineering leaders to make data-driven decisions about resource allocation, tech debt prioritization, and workflow stability.

We’re adding deeper visibility into Work In Progress (WIP) tasks to help teams identify aging work, bottlenecks, and delivery risks in real time. New WIP Metrics Will Include: 🆔 Task ID from Original PM Tool: Reference back to the original task in Jira, ClickUp, etc., for traceability and audit purposes. 📍 Current Status: Shows the latest status of the task (e.g., "In Review", "In QA", etc.) so teams can understand at a glance where work is stalling. 🔁 Cycle Detail: Tracks the path the task has taken through statuses, including transitions and frequency of rework or movement. ⏳ WIP Age: Time elapsed since the task entered an active status (like "In Progress"), allowing teams to quickly detect stale or stuck work. User Value: Spot long-running or forgotten tasks Detect churn or excessive back-and-forth in workflows Improve sprint planning and flow efficiency This enhancement is especially valuable for teams seeking to improve cycle time, flow stability, and predictable delivery.

Get and Post Metrics Data, Updated documentation here https://leanmote.com/docs/set-up/rest-api/

We’re improving how migrated tasks are displayed across sprint tabs to more accurately reflect planning vs. execution behavior in agile teams. 🧠 New Logic: If a task is moved to another sprint before the original sprint becomes active, it will not appear in the original sprint. This respects the sprint planning deadline. If the task is moved after the sprint has started, it will be marked as “Carried Over” or “Sprint Shifted” in the original sprint tab, to signal that the change happened during execution. Tasks completed in later sprints will show a “Carried Over” indicator if they originated in a previous sprint and were moved mid-cycle. Why this matters: Distinguishes between scope changes made before and during execution Helps teams detect tasks that are repeatedly deferred or reprioritized Improves accuracy of sprint completion metrics and flow efficiency tracking

Leanmote connects to Google Calendar & Meet to give leaders a clear view of how meetings impact team performance and costs. Understand if meetings help collaboration or create unnecessary overhead. Detect how much focus time teams actually preserve. Measure meeting load, costs, and participation patterns automatically. Back leadership decisions with data, not guesswork. 🔗 Why Leanmote for Calendar & Meet? Google Calendar tells you when a meeting happens — but not its impact. With Leanmote, every scheduled and recurring meeting is transformed into metrics that show the real cost and efficiency of collaboration: Time lost in recurring or large meetings. Distribution of focus vs. meeting time. Alignment between teams through connectivity graphs. Early detection of overload on certain individuals or groups. ⚡ Real-Time Sync Once connected, all meetings are automatically analyzed: Meeting Hours – Track total time invested in meetings. Focus Time – Measure uninterrupted time left for deep work. Meeting Duration – Spot if meetings run too long. Recurrent Meetings – Detect patterns that eat into productivity. Large Meetings – Identify sessions with too many participants. Meeting Costs – Estimate the hidden cost of meetings in work hours. All data is updated continuously, without any manual reporting. 🌍 Benefits for Your Organization Boost Productivity: Reduce unnecessary recurring and large meetings. Protect Focus: Ensure deep work time isn’t fragmented. Lower Costs: Quantify and cut down on wasted meeting hours. Strengthen Collaboration: See how teams connect and where silos exist. 📌 Typical Use Case A data engineering team spends 8–10 hours weekly in coordination calls. With Leanmote: Meeting patterns are automatically tracked from Google Calendar. Dashboards highlight that 40% of time is lost in recurring sessions. Leaders spot overloaded connectors and reduce meeting frequency. The team recovers focus time, improves delivery speed, and lowers coordination costs. 👉 The outcome: fewer but more effective meetings, better collaboration, and lower costs.

We’re redesigning the Team Interaction Map to better reflect how collaboration happens at scale. The new version will focus on clarity, structure, and directional insights, making it easier to analyze cross-team communication and engagement. Key Improvements: Team-Level Grouping: Users will be visually grouped by their assigned teams, simplifying the analysis of internal vs. external collaboration. Directional Arrows: Arrows will now indicate the direction of interactions, showing who initiates communication and who receives it. Scalability: Optimized for large organizations — the new map will support up to 200 users without performance degradation. Multiple View Modes: Total Interactions View: See all user-level communication across the org. Grouped by Team View: Understand team-to-team relationship dynamics. Enhanced Color Coding & Layouts: Clearer visual clusters and less node overlap to improve usability and pattern recognition. User Value: This improvement will help engineering and people leaders: Detect communication silos or bottlenecks Identify under- or over-engaged teams Improve coordination in distributed or multi-team setups