AI Software Engineering

The Challenges We Tackle at Crombie

Rigid processes that make it hard to adapt quickly to scope changes

Low productivity in distributed or growing teams

Inconsistent code and growing technical debt

Difficulty in scaling without increasing your operational structure

Lack of traceability and up-to-date documentation throughout development

No test automation, leading to rework and production errors

Dependency on key experts and concentration of knowledge.

Missing security and compliance standards integrated into the SDLC

Limited visibility into technical metrics for decision-making

High maintenance costs due to inconsistent codebases

Long development and delivery times

AI Software Solutions Aligned with Your Industry

LLM-Assisted Coding

We code faster and with fewer errors by using AI Pair Programming. The AI suggests, corrects, and optimizes in real time.

Automated Refactoring and Technical Debt Analysis

We reduce technical debt by identifying bottlenecks and optimizing the code with AI agents that suggest sustainable improvements.

Automated Documentations and User Story Documentation

We automatically document processes and use cases. The AI creates living documentation and clear user stories for your team.

Test Automation with Gen AI

We implement automated unit and regression testing. The AI speeds up coverage expansion and prioritizes the most critical scenarios.

Smart Prioritization of Errors and Regressions

We identify and rank errors based on real impact. The AI helps us tackle first what’s affecting your operations more.

ChatOps: Conversational Agents for DevOps

We build conversational assistants that integrate into your DevOps cycle. They help you deploy, monitor, and resolve incidents using simple commands.

AI Agents for L1/L2 Support

We deploy AI agents to handle technical queries and internal tickets. This reduces response times and frees your team to focus on more strategic work.

AI Software Engineering Use Cases

Time-to-market reduction in complex development cycles

We help you speed up delivery times by integrating LLMs and AI Agents at key stages of the development cycle. In internal tests, we reduced onboarding time by 35% and doubled testing coverage in just 3 sprints using GenAI tools.

Technical scaling without increasing headcount

We enable seamless scaling by automating repetitive tasks such as QA, L1 support, and documentation through AI agents. This frees up your team to focus on what truly adds value, even in contexts with tight budgets or limited talent availability.

Benefits of AI Software Engineering

Reduced time-to-market with increased quality

We automate tasks and apply generative testing to accelerate deliveries without compromising stability or technical quality.

Full Visibility into the Development Lifecycle

We deliver real-time metrics and traceability so you can make informed decisions and spot bottlenecks early.

Error and Technical Debt Reduction

We use automated refactoring, best practices, and living documentation to keep your code clean and sustainable over time.

Improved Onboarding and Knowledge Transfer

We speed up the incorporation of new developers with templates, smart guides, and pairing by leveraging AI from day one.

More efficiency without growing the team

We incorporate AI agents that assist in support, QA, and coding, freeing up your team to focus on more strategic work.

Tangible AI Adoption with Real Impact

We implement AI solutions that showcase innovation and deliver visible results for your business and stakeholders.

Our Differentiators

Active CoE and Progressive Framework Adoption

We combine a Center of Excellence model with a step-by-step roadmap to incorporate AI into your SDLC without disrupting existing workflows: from controlled pilots to full-scale deploys.

Co-delivery and Knowledge Transfer

We collaborate with your team at every stage (design, development, testing), offering hands-on training and technical support so that AI adoption becomes embedded, not just another deliverable.

Real Expertise in AI Integration into the SDLC

We work with tools that adapt to your stack and processes, such as Claude, GitHub Copilot, Dev Agents, AWS Bedrock, and Vertex AI.

Reusable AI Toolkits and Prompt Library

We provide ready-to-use assets (refactoring scripts, living documentation templates, AI pair programming agents, generative testing pipelines) that speed up the implementation and ensure consistency across projects.

People-Centered and Ethical Focus

We foster a responsible use of AI to empower your teams, boost their productivity, and preserve human knowledge instead of replacing it.

CodeWhisperer

Contextual code suggestions

DevOps Guru

Automated anomaly detection

CodeGuru Reviewer

Refactoring and performance recommendations

Duet AI for Developers

Generative assistance in the IDE

Cloud Build + AI

Release and testing optimization

GitHub Copilot

Real-time smart pairing

Azure DevOps + AI

Predictive insights in dashboards and pipelines

Flexible and Scalable Hiring Models

Capacity-Based

We provide a dedicated team, fully committed to your project from start to finish. We ensure continuity, understanding of your backlog, and scaling quickly to help you move forward without friction.

Fixed Price

We offer you a fixed price that covers the entire scope and deliverables defined after a thorough discovery phase. Together, we define each milestone and delivery date, giving you full cost and deadline certainty. Perfect for projects with well-defined requirements, where predictability and risk management are key.

Fixed Price per Sprint

You pay a fixed amount for each agreed sprint, with clear objectives and deliverables. Maintain financial control in every iteration without sacrificing Scrum’s agility. Ideal for mature teams seeking visibility on investment and flexibility to reprioritize.

Time and Materials

You only pay for actual hours worked and resources used. Gain full flexibility for exploration, maintenance, or prototypes without long-term commitment. A great fit for early-stage exploration, one-off support, or evolving projects with variable reach.

Frequently Asked Questions About AI Software Engineering

How is AI used in software development?

AI is integrated into key tasks of the development cycle, such as code review, test generation, and automated documentation. Furthermore, it enables early defect detection, accelerates validations, and standardizes technical quality. In this way, teams deliver software faster and with less rework.

How does Crombie work with internal development teams?

Crombie integrates collaboratively with existing teams, respecting already defined processes, practices, and tools. We support AI adoption through workshops, continuous monitoring, and agents trained with internal standards. As a result, the team incorporates AI without friction and with visible improvements starting in the first weeks.

How does AI improve the speed of CI/CD cycles?

AI identifies errors before reaching testing, generates more comprehensive test cases, and automates repetitive validations. Moreover, it prioritizes failures based on impact and reduces false positives, thus accelerating the step from development to deployment. Consequently, CI/CD cycles become faster, more stable, and more predictable.