Andela

Many enterprises still have code spread across Azure DevOps, GitLab, Bitbucket, Jenkins, TFS, SVN or self-hosted servers. That fragmentation slows teams down and keeps them from getting value from GitHub Copilot and agents. Andela consolidates your estate onto GitHub Enterprise Cloud, including moves from GitHub Enterprise Server. A dedicated Andela pod moves code, full history, boards and permissions using GitHub Enterprise Importer and our GitHub Migration Platform, in planned waves so teams keep shipping. We also rebuild CI/CD on GitHub Actions with golden-path templates and switch on secret protection and code scanning as part of the move. Ideal for a consolidation mandate, license renewal, M&A integration or cloud move. - Completed in weeks, not quarters - Typically 30–50% below traditional integrator cost - Full history and review records preserved - A secure foundation ready for Copilot and agents

Many organizations buy GitHub Copilot licenses, but only a few early champions get real value while most engineers stay in manual workflows. The gap is skills, judgment and confidence, not tooling. Andela's Copilot programs are assessment-led and practiced on real code: an enterprise-grade brownfield codebase, with a capstone on your own codebase or ours. Copilot Adopt (101) builds everyday agentic fluency for mid-level and senior engineers in six modules over two weeks or two days, with live workshops, guided practice and a real-world capstone. Copilot Impact (201) is a six-week program for engineers ready for complex workflows: delegation from issue to PR, MCP integrations, multi-agent orchestration, token efficiency and cost governance. Every engineer is assessed at entry and exit, with a 30-day adoption pulse, so we measure proficiency gains and sustained Copilot use, not just course completion. - Proficiency improved from 46% to 78% - 85% of completers active within 30 days - 74% still active weekly at 90 days

Even after code moves to GitHub, many organizations are left with one-off pipeline scripts, inconsistent build steps and security checks that vary by team. Every new project reinvents its path to production, and agents can't reliably automate work without shared standards. Andela rebuilds your CI/CD on GitHub Actions around a small set of standard, reusable workflows. We create golden-path templates for your common build, test and deploy patterns and place them in your repositories, so new projects start on an approved, secure path. Code scanning and secret protection are built in, not added later. We then help teams introduce Agentic Workflows in GitHub Actions for low-risk automation like dependency upgrades, tests and docs. - Standard pipelines instead of bespoke scripts - Templates that enforce security and quality automatically - Faster onboarding for new projects - A foundation ready for agent-driven automation

GitHub's agents can take an issue all the way to a pull request, but most organizations haven't decided what an agent may do alone, how work is handed to it or who signs off on its code. Without those decisions, agent use stalls or grows without control. Andela helps you make those decisions and build them into GitHub. The Playbook puts your rules in writing, agreed with engineering and security leads: what agents may do unsupervised, starting with low-risk work like tests, upgrades, docs and bug fixes; how to write issues an agent can take; how agent code is reviewed; and when work moves from supervised to autopilot. The Templates turn each rule into setup in your repos: custom instructions, custom agents, tuned Copilot code review, Agentic Workflows, and approved tools and MCP servers managed through the Agent Control Plane. Use Copilot, Claude or Codex under one governance model, measured on cycle time, PR throughput and agent-authored PRs merged.

Around 75% of organizations are exploring or deploying AI agents, but only 15% run them autonomously. The blockers are a mix of technical, skills and governance gaps, and it's hard to know which to tackle first. Andela's Agentic Engineering Assessment gives you a data-driven starting point. We review your repositories, pipelines, security posture and Copilot usage, and baseline your engineers' skills using Andela's AI-era skills taxonomy. You get a gap list for each SDLC stage: plan, build, test, review, delegate, automate and secure. Each gap is matched to the work that closes it (migration, training, playbook or templates), then costed and sequenced. Built for organizations evaluating agentic AI or GitHub modernization, especially those with an executive sponsor holding a transformation or AI mandate. - A prioritized investment plan, not a tool list - Scope based on your data, not guesswork - A first phase small enough to approve this quarter