Sold by: Applying Consulting
Applying Consulting helps software teams integrate AI tools into their full development cycle — code generation, automated code review, security scanning, testing, and documentation. Powered by Amazon Q Developer and GitHub Copilot, configured securely for your proprietary codebase.
Overview
Applying Consulting is an AWS Advanced Partner helping engineering teams adopt AI tools across their entire development workflow. Organizations that have already adopted AI in development are producing software significantly faster. Every month without these tools is velocity lost to competitors who are already using them.
This is not about a single tool — it is about transforming how your team builds software across every phase: coding, testing, code review, documentation, debugging, and refactoring.
Three-phase engagement:
Phase 1 – Assessment: Evaluation of current development process, identification of bottlenecks where AI generates the greatest impact, and tool recommendation based on the team's context and existing stack.
Phase 2 – Implementation: Configuration of AI tools in the team's development pipeline:
- Amazon Q Developer: AI code assistant integrated in IDE (VS Code, JetBrains). Code generation, debugging, code explanation, and legacy code transformation. Automated code review with SAST security analysis, secret detection, dependency vulnerability scanning (SCA), and code quality checks. Integrates with GitHub and GitLab for pull request reviews.
- GitHub Copilot: Real-time code autocompletion for teams already working with GitHub.
- Amazon Inspector: Continuous security scanning of code repositories (GitHub/GitLab) for vulnerabilities in code and dependencies.
Phase 3 – Adoption: Practical workshops, pair programming with AI, adoption metrics, and productivity measurement. Accompaniment until AI becomes a natural part of the team's workflow.
Security configuration: We configure all tools to protect proprietary code — defining what is shared with AI models and what stays private. This addresses the primary concern of CTOs considering AI tools for the first time.
Business impact: Reduce development time through AI-assisted code generation and autocompletion. Reduce production bugs through automated code review. Reduce documentation and testing time through AI generation. The team focuses on business logic, not repetitive code.
This service relates to Amazon Q Developer, Amazon Inspector, AWS CodePipeline, AWS CodeBuild, GitHub Actions, Azure DevOps, and Amazon Bedrock.
Highlights
- Integrate Amazon Q Developer and GitHub Copilot into your team's full development cycle: code generation, automated code review (SAST, SCA, secret detection), security scanning, testing, and documentation — configured securely to protect your proprietary codebase.
- Three-phase engagement: assessment of bottlenecks, AI tool implementation in your existing pipeline, and adoption accompaniment through pair programming and practical workshops until AI becomes natural workflow — not a forced tool.
- Teams that have adopted AI in development produce software significantly faster. Every month without these tools is velocity lost to competitors already using them. AI for the development cycle is not the future — it is the new productivity baseline.
Details
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Support
Vendor support
Applying Consulting provides assessment, implementation, and adoption support across all three phases of the engagement.
Support channels:
- Email CO: sales.colombia@applying.cloud
- Email PE: sales.peru@applying.cloud
- Website: https://www.applying.cloud
- Business hours: Monday to Friday, 9:00 AM – 6:00 PM (Lima, Peru / Bogotá, Colombia)
- Service delivery language: Spanish
Support scope: Buyers receive a development process assessment, AI tool recommendation, secure configuration of Amazon Q Developer and/or GitHub Copilot, integration with existing CI/CD pipeline, practical adoption workshops, and productivity metrics setup. Duration: 4–8 weeks. Available as project or ongoing retainer.