Developer productivity

Measure developer productivity.
From real delivery data.

PR cycle time, throughput, review time and work in progress, collected automatically from your Git and issue tools. Then see how AI coding tools move them. No surveys, no lines of code.

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14-day free trial on every plan, no credit card required.

Explore
AdoptionImpactCostsAI score
PR throughput184 / mo
PR cycle time1d 9h
AI active users42
AI tokens ▾compared toPR throughput ▾
AI tokensPR throughput
Illustrative data
What you measure

Productivity is flow.Not lines of code.

Axify tracks how work moves, from first commit to merge, for every team. The same definitions everywhere, with nothing to enter.

PR cycle time

From first commit to merge, split into coding, pick-up and review, so you see where work waits.

Pull requests cycle time breakdown
1d 9hrs +18%
Based on 412 merged pull requests
Coding 11hPickup 14h +75%Review 8h

Throughput

Merged PRs and completed issues per period, by type of work, so you see what the team actually ships.

Issue throughput
96this month
Feature 52%Bug 28%Tech debt 20%
AprMayJunJul

Code review

Time to first review, review time, comments per review and PRs merged without an external review.

Code review
Pick-up time14h
Comments / review3.2
Self-reviewed PRs6%
PRs waiting for a first review
1payments#12882d 4h
2mobile#9041d 2h
3platform#3775h

Work in progress

Open PRs and issues by team. Too much work in parallel slows everything else down.

PR work in progress
38open PRs
Payments14
Mobile10
Platform8
Search6
Illustrative data
Productivity and AI

AI on one side.Delivery on the other.

A license doesn’t make anyone more productive. Axify puts real AI tool usage next to delivery metrics, so you see where AI helps and where it sits unused.

ADOPTION

Who uses AI, and how much

An adoption score out of 100 by contributor and team, across GitHub Copilot, Cursor, Claude Code and LiteLLM.

IMPACT

What changes in delivery

AI usage next to PR throughput, issue throughput and deployment frequency, for the same teams.

FOLLOW-UP

Where to offer support

The biggest gains and drops over 30 days, so you know who to support before the gap grows.

Axify Intelligence

See what moved.Then ask why.

Open the list of pull requests behind every number, then ask Axify Intelligence, in the app or from Claude, ChatGPT and Cursor through the MCP server.

Axify Intelligence
“Why did Payments PR throughput drop?” Payments has 14 PRs open at once, up from 8 last month. Pick-up time went from 8h to 14h: PRs wait longer for a first review.
Axify Intelligence → MCP server →
Pull requests
Payments ▾Last 30 days ▾
Pull requestSizePickupCycle time
payments#1288Checkout refactorLarge2d 4h3d 6h
payments#1281New refunds APIMedium1d 1h2d
payments#1276Currency fixSmall6h14h
payments#1270Dependency updateSmall2h9h
Illustrative data
How it works

A productivity view.In three steps.

STEP 01

Connect your delivery tools

GitHub, GitLab, Bitbucket, Azure DevOps and Jira, read-only. You map your board columns once.

GitHubGitLabBitbucketAzure DevOpsJira
STEP 02

Connect your AI tools

GitHub Copilot, Cursor, Claude Code and LiteLLM. LiteLLM also covers models routed through your proxy.

GitHub CopilotCursorClaude CodeLiteLLM
STEP 03

Compare and act

Follow trends by team, spot where work waits and see whether your changes move the numbers.

Customer results

Less waiting, more shipping.

51%

Up to 51% faster delivery in 3 months

The Business Development Bank of Canada (BDC) cut its delivery time by shifting QA left and working in smaller stories.

Read the case study →
−60%

60% shorter PR cycle time

And 22X more deliveries in 5 months, after a team reorganization and automated deployment.

Read the case study →
Related features

Go further.

AI ADOPTION & IMPACT

Measure AI adoption

The adoption score, its three pillars and the link to delivery.

Explore AI adoption →
AI COST & FORECASTING

Track what AI costs

Cost by tool, model, team and contributor, with a projected trend.

Explore AI cost →
ENGINEERING METRICS

All your metrics

PRs, issues and DORA in one dashboard, by team and project.

Explore engineering metrics →

Frequently asked questions

How does Axify measure developer productivity?
From the data in your Git and issue tools: PR cycle time and its phases, throughput, review time, PR size and work in progress. No surveys and no manual entry.
Does Axify measure lines of code or individual output?
No. Axify tracks flow and delivery outcomes, not vanity metrics like lines of code.
How does Axify show the effect of AI coding tools on productivity?
In Explore, AI usage (active users, tokens) sits next to PR throughput, issue throughput and deployment frequency, for the same teams and periods. You see the trends side by side.
What is the AI adoption score?
A 0 to 100 score built on three pillars, Reflexive use, Reliance and Trust, compared to a reference cohort. It breaks down by contributor, team, project and group.
Which AI tools are supported?
GitHub Copilot, Cursor, Claude Code and LiteLLM. With LiteLLM, any model routed through your internal proxy is covered.
Does Axify read our code or prompts?
No. Every integration is read-only and only shares usage metadata, tokens and cost.
Which plan includes it?
Developer productivity is included in the Pro and Enterprise plans. Every plan starts with a 14-day free trial, no credit card required.

See where work waits.

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