Work Classification lets you define how your organization's engineering work is grouped — above issue types. Create Categories and Subcategories, map your work item types to them, and immediately see the results in two new Project Financials charts.

Investment Allocation Trend — stacked bar chart showing how cost splits across work categories over weeks, months, or quarters

Budget Breakdown — donut chart showing which work types consume the most budget in the current period

Ships with the Roadmap default category (Bug, Epic, Feature, Improvement, Research, Support, Task)

Add your own categories — model the Investment Balance Framework (KTLO / Build / Improve / Productivity) or any accounting structure relevant to your business

Admin only, configured at the organization level · Settings → Work Classification

Discoveries is the place where Leanmote shows you every entity it automatically detected across your integrations so you can decide what to do with each one: accept it, map it to an internal user, or ignore it.

Think of it as your configuration inbox: anything new that shows up in GitHub, GitLab, Jira, Slack, or Calendar and that Leanmote doesn't yet know how to interpret lands here, waiting for your decision.

5 tabs: People, Repositories, Boards, Statuses, Channels

Pending / Ignored / Accepted state filters so you always know what needs attention

Manual trigger: hit "Discover" to run an immediate extraction right after connecting a new integration

Auto-runs every day at 7:00 AM and 7:00 PM

Admin & Owner access only

No more hunting through Settings to find unmapped repos or unknown contributors. Everything surfaces in one place.

AI is no longer just a sidekick to your developers — it now opens PRs, moves Jira tickets, and burns through tokens on its own. brings everything you need to govern that reality in one dashboard: who uses what, what it costs, what it ships, and now — what your are doing alongside your humans.

The dashboard has grown into four tabs that answer four very different questions, plus a new pipeline for ingesting agentic activity at scale.

> sidebar → , or open in your workspace. Filters and date range work across every tab.

We've added a dedicated tab to track autonomous agents (Claude, GitHub bots, custom Jira agents, …) as first-class actors on your team. Identify each agent by the user account it logs in with, then measure its output, quality and cost.

We've reworked our Claude Code data pipeline so per-session activity, model selection, and token usage land faster and more reliably in AI Governance. If you've integrated Claude Code via OTLP, you should see fresher numbers across , , and without doing anything on your side.

If you haven't opened the dashboard in a while, here's what each of the four tabs answers:

All four tabs share filters (date range, projects, work items, teams) and a unified data model — so an agent account counts toward Tokens Consumed on AI Usage, Cost on AI ROI, and Tasks Completed on AI Agents, all at once.

Have feedback or a use case we should support? Reply on Canny, or ping us in your Intercom Messenger inside the app.

Leanmote now supports as a first-class integration — bringing the same depth of engineering analytics to teams using Microsoft's DevOps platform as we've long offered for GitHub, GitLab, and Bitbucket.

## What Gets Connected

With a single OAuth connection, Leanmote syncs data from two Azure DevOps surfaces:

## How to Connect

Once connected, your Azure DevOps data flows into all the same dashboards your team already uses: Performance Delivery, Project Financials, Strategic Overview, and more.

## Who This Is For

Any engineering team that uses Azure DevOps as their primary platform — whether for repositories, project tracking, or both — can now get the full Leanmote experience without needing to migrate tools or maintain manual exports.

If your organization uses a mix of Azure DevOps and GitHub (or other platforms), Leanmote handles multi-source setups automatically, combining data across all connected integrations into a single unified view.

## Why It Matters

Azure DevOps is widely adopted across enterprise engineering teams, particularly in organizations with Microsoft-centric infrastructure. This integration removes the last barrier for those teams to adopt Leanmote's engineering intelligence platform without changing their existing toolchain.

Leanmote now includes — a dedicated dashboard available in both and that answers the question every engineering leader is asking:

## AI Impact in Performance Delivery

The AI Impact section in Performance Delivery is split into two views:

### Delivery Correlation

This view connects AI usage data directly to your team's delivery metrics, surfacing three key signals:

- — lines produced via tab-style completions (e.g., Copilot suggestions accepted by the developer)

- — lines written directly by an AI agent flow, with minimal manual editing

This distinction matters: delegation is a stronger signal of AI reliance than assistance. The dashboard shows the split as a percentage and tracks how it evolves over time.

### Adoption & Usage (AI Impact - Others)

This view gives you the raw adoption data behind the signal:

## AI Impact in Project Financials

The AI Impact tab in Project Financials adds a financial lens to AI usage:

## How to Connect AI Data

AI Impact works with (with Copilot telemetry enabled) and . Once connected via Productivity Tools, metrics appear automatically — no additional setup needed.

## Why It Matters

AI tools represent a significant and growing investment for engineering teams. AI Impact gives you the data to move beyond anecdotal evidence and measure — with real delivery and financial data — whether that investment is paying off.

We're launching — a new AI-powered module that automatically detects where your engineering workflows are slowing down, before those slowdowns turn into missed deadlines or frustrated teams.

## What Is Bottleneck Insights?

Bottleneck Insights continuously analyzes your engineering data and surfaces the patterns that are degrading delivery performance. Instead of waiting for someone to notice that velocity is dropping or PRs are piling up, the AI proactively identifies the root causes and brings them to your attention.

## What It Detects

The AI looks across your full delivery workflow and flags issues like:

## How It Works

Bottleneck Insights runs in the background and surfaces findings with a dedicated section in the product where you can browse current and recent bottlenecks, each with supporting data and a plain-language explanation of what's happening.

Each insight includes the context needed to act: which team, which repo, which time period, and what the expected baseline was. No manual analysis required.

## Why It Matters

Engineering teams generate enormous amounts of delivery data, but the signal is often buried in the noise. Bottleneck Insights applies AI to do the hard work of pattern recognition — so your engineering leaders spend less time diagnosing and more time removing blockers.

This is the first module in Leanmote's track, with more AI-driven analysis coming throughout the year.

now includes engineering performance data alongside investment information — giving engineering leaders and finance stakeholders a single place to understand not just is being spent, but it's being delivered.

## What's New: DORA Metrics in Project Financials

The four DORA metrics are now surfaced directly within Project Financials for each project or initiative:

Seeing these metrics in context with project spend lets you answer questions like:

## What's New: PR Activity in Project Financials

In addition to DORA, is now visible per project:

## Why the Combination Matters

Traditionally, engineering investment data and delivery performance data lived in separate tools and separate conversations. By bringing them together in Project Financials, Leanmote enables a new kind of analysis:

This update is available for all projects tracked in Project Financials. No additional setup required — if your repositories are already connected, the metrics will appear automatically.

We've significantly expanded the dashboard with two major upgrades: a full Cycle Time breakdown and a new set of advanced filters — giving engineering teams and their leaders the precision they need to identify exactly where work slows down.

## Full Cycle Time Breakdown

Cycle Time now goes beyond a single number. It's broken down into its four key stages, so you can pinpoint where delays are happening in your delivery pipeline:

Understanding which stage is the bottleneck is the first step to fixing it. A long Review Time points to a code review process problem. A long Deploy Time might signal a slow CI/CD pipeline. Now you have the data to act on the right thing.

## Advanced Filters: Branch, Author & More

The Software Delivery dashboard now supports a richer set of filters so you can slice data with more precision:

These filters work in combination, so you can ask questions like:

## Why It Matters

Generic averages hide the real story. With Cycle Time broken down by stage and advanced filters, teams can have more targeted conversations about where to improve — and leaders can track whether those improvements are working over time.

We're introducing — a new high-level module designed for engineering leaders who need a consolidated, real-time pulse on their entire organization without jumping between dashboards.

## What Is Strategic Overview?

Strategic Overview is a command center that surfaces the most critical signals across your engineering org in a single screen. Instead of drilling into individual team or project dashboards, leaders can now get an at-a-glance view of:

## Who Is It For?

Strategic Overview is built for CTOs, VPs of Engineering, and engineering managers who are responsible for multiple teams or the full org. It's the answer to the question: — without needing to ask anyone.

## How to Access It

Navigate to in the main menu. You can customize which metrics and teams are visible using saved views, and share the view with other leaders using a public link or team share.

## Why It Matters

Before Strategic Overview, getting a cross-team picture of engineering health required either manual reports or switching between multiple dashboards. Now, everything your leadership team needs to make fast, informed decisions is in one place — always up to date, no prep required.

You can now save, share, and duplicate custom views in Performance Delivery and Project Financials — making it easy to collaborate with your team, align stakeholders, and build on existing configurations without starting from scratch.

## Personal Saved Views

Each user can create and save their own private dashboard configurations. Saved views capture your filters, metrics, and layout so you can return to them in one click — no need to reapply settings every time.

## Share Views with Your Team

Collaboration is now built in. Once you've saved a view, you can share it in three ways:

## Duplicate Views

Need a similar configuration with small tweaks? Duplicate any existing view and modify it without affecting the original. This is especially useful for creating variants (e.g., one view per team or project) based on a standard template.

## Where It's Available

Share and Duplicate are available in both and dashboards.

## Why It Matters