Helping development teams deliver faster with less friction
The bottleneck was never code. It was governance gaps, workflow fragmentation and context lost between teams. We fix the architecture that unlocks your engineering talent.
Why capable teams still struggle to deliver
Talented developers lose productivity to workflow friction, not skill gaps. AI tooling without the right architecture delivers only marginal gains.
Inconsistent Environments
Manual approvals and fragmented toolchains burn developer hours before meaningful code is written.
Marginal AI Gains
Copilot is in place, but without structured workflows the efficiency gain from idea to live feature stays limited.
Context Lost in Handoffs
Decisions buried in threads. Rationale relitigated three sprints later. Handoffs are where velocity dies.
Discretionary Governance
Compliance depends on individual discipline rather than architectural enforcement — a risk that scales with headcount.
Fragmented Toolchains
Sprawl across Azure DevOps, GitLab and GitHub creates maintenance overhead and blind spots for engineering leaders.
AI Adoption Stalls
Without a governed platform foundation, enterprise AI adoption peaks early and then underdelivers on its promise.
Customer Testimonial
Steps
Three stages. One governed engineering platform.
Governance is architectural. AI amplifies well-governed practices. Seniors define boundaries, agents operate within them, every engineer does higher-value work.
01
Governed GitHub Enterprise Platform
Opinionated org, repo and environment structure with branch protection, CODEOWNERS and SSO. Advanced Security from day one — secret protection, code scanning and supply chain governance baked in.
02
AI Workflows & Copilot Enablement
Establish unified governance with Microsoft Purview and Agent 365 for centralized control, observability, and compliance across your AI estate.
03
Full Lifecycle Agentic SDLC
Apply Zero Trust principles to AI systems with identity-based access, least privilege enforcement, and continuous verification across the AI lifecycle.
The Process
What we implement and how it works
Four integrated capability areas that build on each other — from governed foundation through to full agentic delivery at scale.
Governed GitHub Enterprise Platform
An opinionated org structure built for governance and scale. Every configuration decision is documented, reviewable and repeatable — from branch protection rulesets to environment secrets.
- Org & repo structure design
- Branch protection & CODEOWNERS
- SSO / SAML integration
- Enterprise compliance policies
- SDLC pattern from branch to release
Security Embedded in Every Commit
Advanced Security is enabled from day one — not bolted on after delivery. Secret protection, code scanning and supply chain security become part of the developer workflow.
- Secret scanning & push protection
- Code scanning (SAST / IaC)
- Dependabot alerts & auto-PRs
- Software composition analysis
- Security overview dashboards
AI Amplification for Your Entire Team
Structured Copilot adoption with usage measurement, champions networks and role-specific labs. GitHub Actions pipeline migration with governed deployment pattern libraries.
- Role-specific Copilot labs
- Usage analytics & adoption tracking
- Champions & guild programmes
- Actions pattern library creation
- PR-based deployment governance
DevOps & GitLab Migration at Scale
Specialised AI agents migrate repositories, pipelines, work items and configurations from Azure DevOps or GitLab to GitHub Enterprise. Structured, auditable, designed for large estates.
- Repository migration at scale
- Pipeline conversion to Actions
- Work item & history transfer
- Configuration parity validation
- Cutover playbook & rollback plan
Meeting transcripts become production-ready code. AI agents handle requirements, architecture, estimation, implementation, testing, approvals and operations — with experienced engineers overseeing every stage.
Transcripts → structured requirements. AI drafts, senior validates.
Automated ADR generation with governance boundaries defined by seniors.
AI-assisted sizing with risk flags surfaced for human review.
Copilot-augmented development within governed branch workflows.
Automated test generation, coverage enforcement and quality gates.
Approval checkpoints, audit trails and compliance artefact generation.
Runbook generation, incident pattern detection and feedback loops.
Human-in-the-loop at every critical gate.
Agents execute and recommend; experienced engineers define governance thresholds, review risk flags and make approval decisions. The workflow builds judgement across teams — not dependency on AI.
Outcomes across your Engineering Organisation
Security, compliance and quality gates embedded into how the platform works — not dependent on individual discipline.
Automated pipelines, governed deployments and agentic workflows compress time from idea to live feature.
Usage analytics, champions programmes and productivity benchmarking — not just licences, but meaningful adoption across roles.
Reusable, governed workflow templates that standardise deployment patterns and scale without fragmentation.
Structured programmes for 25 or 100 developer cohorts — seniors build governance design skills, developers build AI judgement.
AI agents embedded from requirements through to operations — with human-in-the-loop oversight at every governance checkpoint.
GitHub Enterprise AI Ready Foundation Build
A governed foundation in three weeks — for one pilot team
- Running AI-ready GitHub Enterprise Cloud foundation for one pilot team
- Opinionated org, repo and environment structure with branch protection and CODEOWNERS
- Secret protection, code scanning and Dependabot configured and active
- SDLC pattern wired from development branch to deployment, with hooks for Copilot and Actions
- AI-enabled SDLC blueprint and governance model for the full organisation
- Security and governance framework documentation
- Org and repo patterns designed for scale beyond the pilot
- Prioritised backlog for Copilot adoption, Actions migration and DevOps consolidation
A working AI-ready GitHub foundation for one pilot team, plus the blueprint for scaling across the organisation. Every configuration decision is documented, repeatable and designed to grow.
Duration
3 weeks
Scope
~25 developers
Funding
Microsoft eligible
Deep expertise. Proprietary platform. Real results.
Agile Insights combines deep experience across cloud platforms, automation, governance, GitHub Enterprise and modern engineering practices. We developed Agile SDLC — a proprietary agentic platform that embeds AI agents into structured software development workflows with architectural governance.
This is not a services business that wraps GitHub licensing in a statement of work. We have opinionated views on how engineering organisations should operate — and the implementation capability to make those views real inside your organisation.
Frequently Asked Questions
What is developer productivity platform engineering?
What does the Agentic Migration Factory actually do?
Zero Trust for AI extends traditional Zero Trust principles to autonomous agents and AI applications. This means treating AI agents like human users with explicit verification, least privilege access, and continuous monitoring. We assign unique Agent IDs through Microsoft Entra, enforce Conditional Access policies that include risk-based decisions, implement network segmentation with private endpoints, and apply scoped service accounts for tool execution. Zero Trust for AI also includes continuous security monitoring through Microsoft Sentinel, real-time threat detection via Defender for AI, and DLP policies that prevent agents from accessing or outputting sensitive data. The goal is to ensure that even if an agent is compromised, the blast radius is limited by strong identity controls and least privilege enforcement. It deploys specialised AI agents to migrate repositories, pipelines, work items and configurations from Azure DevOps or GitLab to GitHub Enterprise at scale. Migrations are structured, auditable and validated for configuration parity.
Is the GitHub Enterprise Foundation Build really Microsoft-funded?
Why GitHub Enterprise over other platforms?
How does Copilot enablement differ from just buying licences?
How does human-in-the-loop governance work in the Agentic SDLC?
Ready to build the platform your engineers deserve?
If developer productivity, GitHub adoption or AI-augmented engineering are on your roadmap, the conversation starts with a governed foundation.