DevNala by CloudNala
Turn developer activity into engineering intelligence.
DevNala helps software teams improve delivery, documentation, DevOps maturity and AI-assisted development by connecting engineering signals, workflows and knowledge into one practical productivity layer.
PR Cycle Time
2.4 days
↓Doc Coverage
62%
↑Deploy Frequency
Weekly
→Copilot Adoption
Growing
↑AI Recommendation: Improve onboarding docs for API projects to reduce ramp-up time.
Most teams are busy shipping, but few can clearly see how engineering is improving.
Delivery data is scattered across tools
Documentation becomes outdated quickly
AI adoption is hard to measure
DevOps maturity is discussed but not tracked
Engineering knowledge lives in people's heads
Leaders struggle to connect activity to business outcomes
DevNala connects engineering signals into practical decisions.
DevNala helps engineering teams and leaders turn scattered data into actionable insight:
Understand delivery bottlenecks and cycle time
Improve developer experience and reduce friction
Track DevOps maturity across teams and projects
Support GitHub Copilot adoption and measure impact
Build reusable engineering knowledge and runbooks
Improve documentation quality and onboarding
Identify opportunities for automation and tooling improvement
Connect engineering work to business value and outcomes
From engineering signals to continuous improvement.
Connect delivery signals
Bring together engineering signals from tools like GitHub, Azure DevOps, documentation repositories, project notes and delivery workflows into one connected layer.
Analyse team productivity
Identify bottlenecks, repetitive work, documentation gaps, quality issues and improvement opportunities across teams and repositories.
Use AI to generate insights
DevNala uses AI to summarise patterns, recommend improvements, and help teams turn scattered knowledge into reusable guidance and documentation.
Improve continuously
Teams use DevNala to track improvements across delivery speed, documentation quality, DevOps maturity and AI-assisted development adoption.
Engineering intelligence across the full delivery lifecycle.
Developer Productivity Dashboards
Visualise delivery metrics, cycle times and engineering health across teams and repositories.
GitHub Copilot Adoption Insights
Track Copilot usage, measure productivity impact and guide adoption across engineering teams.
Azure DevOps & GitHub Workflow Analysis
Analyse pull request flow, pipeline health and deployment patterns to surface improvement areas.
Pull Request & Delivery Flow Visibility
Understand where code slows down — review time, rework, blocked PRs and deployment bottlenecks.
Engineering Documentation Intelligence
Assess documentation coverage, identify gaps and generate improvement recommendations for codebases.
DevOps Maturity Assessment
Benchmark team practices against DevOps maturity dimensions and track improvement over time.
Team Onboarding Knowledge Base
Build and maintain structured onboarding content so new developers ramp up faster.
Architecture & Technical Debt Insights
Surface architectural risks, dependency issues and technical debt patterns across the codebase.
AI-Assisted Delivery Recommendations
AI-generated recommendations for delivery improvement, workflow automation and team enablement.
Sprint & Delivery Retrospectives
Generate structured retrospective summaries and track improvement actions across sprints.
Platform Engineering Support
Support internal developer platform teams with tooling intelligence, usage metrics and improvement guidance.
Executive Engineering Reports
Clear, non-technical summaries of engineering health, delivery trends and improvement progress for leadership.
Built for engineering leaders and the teams they lead.
GitHub Copilot Adoption Programmes
Measure, guide and report on GitHub Copilot rollout across engineering teams.
DevOps Maturity Improvement
Assess current DevOps practices and track measurable improvement across delivery dimensions.
Engineering Leadership Dashboards
Give CTOs and Heads of Engineering clear visibility into delivery health and team productivity.
Developer Onboarding
Reduce ramp-up time with structured knowledge bases, documentation and guided onboarding.
Technical Documentation Improvement
Identify gaps in API docs, runbooks, architecture records and developer guides — then fix them.
Architecture Knowledge Base
Build and maintain a living architecture knowledge base aligned to actual system behaviour.
Software Delivery Improvement
Improve cycle time, reduce rework and increase deployment frequency with data-driven insights.
Internal Developer Platform Enablement
Support IDP teams with tooling intelligence, adoption metrics and developer experience improvement.
AI-Assisted Engineering Transformation
Guide organisations through AI-assisted development adoption with structured enablement and measurement.
Built for modern Microsoft-aligned engineering teams.
Aligned to Microsoft, Azure, GitHub and modern DevOps ways of working.
GitHub Copilot Enablement
Support teams adopting GitHub Copilot with measurement, guidance and adoption dashboards.
Azure DevOps Workflows
Analyse pipelines, boards, repositories and delivery workflows in Azure DevOps environments.
GitHub Repositories & Pull Requests
Connect to GitHub to analyse contribution patterns, PR flow and code review health.
Azure Cloud-Native Delivery
Support engineering teams building on Azure with cloud-native delivery intelligence.
DevOps & Platform Engineering
Aligned to DevOps Research and Assessment (DORA) metrics and platform engineering best practices.
Engineering Governance & Reporting
Provide structured reporting for engineering governance, compliance and continuous improvement.
DevNala is independently designed by CloudNala. It is not an official Microsoft or GitHub product. DevNala is aligned to Microsoft, Azure and GitHub ways of working.
From activity tracking to engineering intelligence.
Activity tracking tells you what happened. Engineering intelligence helps you understand what to improve.
DevNala helps engineering leaders answer these questions with data — not guesswork. It connects delivery signals, documentation, team practices and AI adoption into one practical improvement layer.
Responsible AI for engineering teams.
AI supports, teams decide
AI assists with analysis, summarisation and recommendations. Engineering leaders and teams remain in control of all decisions.
Secure code and document handling
Sensitive code and documents must be handled securely. Access to engineering data should be role-based and clearly scoped.
Clear data purpose
Engineering data is collected for clear improvement purposes — delivery optimisation, documentation and team enablement.
Not a surveillance tool
DevNala should be used to improve systems, workflows and team enablement — not to unfairly monitor or penalise individual developers.
Team improvement focus
Insights are designed to improve teams and systems — not to rank or blame individual contributors.
Transparent AI recommendations
AI recommendations are presented as suggestions. Teams can review, reject or refine any AI-generated insight.
DevNala is designed to support engineering improvement and responsible AI adoption. It should be used to improve systems, workflows and team enablement — not to unfairly monitor or penalise individual developers.
Start with one team. Prove the insight. Then scale.
DevNala can start as a focused pilot for one engineering team, one repository, one Azure DevOps project, or one GitHub Copilot adoption programme. Once the value is proven, it can scale into a broader engineering intelligence platform.
DevNala by CloudNala