AI-Augmented Engineering for Enterprise GRCAI-Augmented Engineering for Enterprise GRC

The client is a global Governance, Risk, and Compliance software leader behind one of the world's leading GRC platforms, serving over one million users across 35 countries. Its platform supports risk management, compliance, audits, and cybersecurity through 16 specialized products.

The platform serves complex enterprise environments through a highly configurable model designed around industry-specific requirements.

The core business risk was customer churn. Enterprise customers expected faster customization, smoother deployments, and quicker feature releases, but the platform's highly configurable model was creating delivery strain.

The client needed to reduce repetitive engineering effort, improve developer productivity, modernize legacy components, and make customer-specific changes easier to deliver without disrupting live enterprise environments.

The client had to address several platform and delivery constraints before it could improve responsiveness across customer environments.

1. Heavy customization depended on direct code edits across forms, workflows, and rules.
2. Customer-specific implementations made upgrades difficult to replicate and standardize.
3. Legacy JavaScript rules and Backbone.js components slowed development and made change cycles harder to manage.
4. Manual setup, fragmented tooling, and reliance on tribal knowledge slowed onboarding and reduced team autonomy.
5. Deployment and release processes needed stronger standardization to support faster, safer delivery.

Modernizing a live GRC platform meant working inside compliance-critical customer environments. The client needed a partner who could improve delivery speed without weakening governance, quality, or release stability.

Coditas brought together AI-augmented Engineering, Legacy Modernization with AI, UX design, and DevOps discipline across one program. Multi-Agent Systems were applied through rule standardization agents, sub-agent workflows, and human-reviewed customization support, giving teams a safer way to reduce repetitive effort and accelerate change.

Coditas delivered a phased modernization program focused on reducing repetitive engineering work and simplifying customer-specific customization.

Our team built AI-assisted workflows for rule standardization, form customization, workflow changes, and troubleshooting. Agents and sub-agents converted high-frequency configuration tasks into structured, reviewable workflows, while human approval remained in place for critical changes.

In parallel, Coditas migrated Backbone.js components to React, improved the platform's modular architecture, redesigned the admin experience around role-specific tasks, and strengthened DevOps practices for safer deployments across enterprise customer environments.

Java, Groovy, JavaScript, Backbone.js, React, AWS EC2 INF2, Llama CPP, DeepSeek, Docker, MCP, Figma, Rule DSL

The engagement improved productivity, reduced manual coding effort, accelerated modernization, and strengthened delivery stability.

• 25% productivity boost from the Rule Standardization Agent
• 40% reduction in manual coding effort for form and rule customization
• 50% faster onboarding for new developers through modular architecture
• 100% migration from Backbone.js to React
• 30% faster modernization cycles using AI agents and sub-agents
• 3x faster admin task completion through role-specific layouts and embedded guidance
• 50% reduction in administrator training time
• Zero service disruptions during platform upgrades

Mature enterprise platforms rarely need AI in isolation. They need AI applied to the repetitive work that slows teams down, creates upgrade friction, and increases delivery risk.

For the client, our engagement turned customization, rule management, modernization, and admin workflows into faster, more structured, and reviewable processes without compromising release stability.